CN114564471A - Grading method and device for laser radar system - Google Patents

Abstract

The present application provides a classification method and device for a lidar system. The method includes: acquiring a target data set; eliminating invalid data in the target data set to obtain a target-screened data set; performing capture matrix statistics on the target-screened data set to obtain Statistical results corresponding to the data set after target screening; according to the statistical results corresponding to the data set after target screening, determine whether the number of statistical values contained in the target screening data set meets the preset number requirement; if so, the corresponding data set after target screening is determined. Statistical results, determine whether the target lidar system is mature; if the target lidar system is mature, calculate the uncertainty accuracy level of the target lidar system according to the target screening data set. It can be seen that the present application can calculate the uncertainty accuracy level of the target lidar system.

Description

A classification method and device for a lidar system

technical field

The present application relates to the technical field of lidar systems, and in particular, to a classification method and device for lidar systems.

Background technique

With the development of offshore wind resources exhausted, the development of offshore wind resources has become an inevitable trend. The water depth in the open sea is relatively large, and the erection of traditional anemometer towers has a long period and high cost. With the substantial improvement of the reliability and performance of the lidar system, and the further shortening of the maintenance time and cycle, the lidar system will be used as a fast and convenient in the future. The new offshore wind measurement equipment has certain economic, technical and time advantages.

The uncertainty contained in the classification of the lidar system can be used to characterize the difference between the meteorological data measured by the lidar system and the real value. The estimation range of this uncertainty is very important to the profitability of the wind farm operation in the later stage, but At present, there is no method to calculate the uncertainty of lidar system in the industry.

To sum up, a classification method of lidar system is urgently needed to determine the uncertainty accuracy level of lidar system.

SUMMARY OF THE INVENTION

In view of this, the present application provides a classification method and device for a lidar system, which are used to calculate the uncertainty accuracy level of the lidar system, and the technical solutions are as follows:

A classification method for a lidar system, comprising:

Obtain a target data set, wherein the target data set includes at least three data sets consisting of statistical values of data collected by two lidar systems of the same model and anemometer towers located in two sea areas under set conditions, and the statistical values at least include Wind speed statistics, setting conditions include at least one wave height;

Eliminate invalid data in the target data set to obtain the target filtered data set;

Perform capture matrix statistics on the target-screened data set to obtain statistical results corresponding to the target-screened data set, wherein the capture matrix is used to count the number of statistic values whose wave heights are in each preset wave height interval and the wind speed statistical value is in each preset wind speed interval. and the total number of statistical values and the number of wave height intervals in each preset wind speed interval, the number of wave height intervals in a preset wind speed interval refers to the preset wind speed interval whose number of statistical values is greater than or equal to the first number The number of wave height intervals;

According to the statistical results corresponding to the target-filtered data set, determine whether the number of statistical values contained in the target-filtered data set meets the preset number requirement;

If satisfied, determine whether the target lidar system is mature according to the statistical results corresponding to the data set after target screening, wherein the target lidar system includes at least two lidar systems of the same model;

If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated according to the filtered data set of the target.

Optionally, also include:

Determine the data efficiency according to the target filtered data set and the target data set;

According to the data efficiency, it is determined whether the target lidar system is mature, so that when the target lidar system is mature, the capture matrix statistics are performed on the data set after target screening, and the statistical results corresponding to the data set after target screening are obtained.

Optionally, the target filtered data set includes at least three filtered data sets corresponding to the three data sets respectively;

Perform capture matrix statistics on the target-screened data set to obtain statistical results corresponding to the target-screened data set, including:

For each screened data set included in the target screened data set, perform capture matrix statistics on the screened data set to obtain the statistical results corresponding to the screened data set; to obtain each screened data set contained in the target screened data set The statistical results corresponding to the data sets;

According to the statistical results corresponding to the target filtered data set, determine whether the number of statistical values contained in the target filtered data set meets the preset quantity requirements, including:

For each filtered data set included in the target filtered data set, according to the statistical result corresponding to the filtered data set, determine whether the number of statistical values contained in the filtered data set meets the preset number requirement;

Determine whether the target lidar system is mature according to the statistical results corresponding to the data set after target screening, including:

For each screened data set included in the target screened data set, according to the statistical results corresponding to the screened data set, determine whether the lidar system corresponding to the screened data set is mature; to obtain each target screened data set included in the Whether the lidar system corresponding to each filtered data set is mature;

If the laser radar system corresponding to each filtered data set included in the target screened data set is mature, it is determined that the target laser radar system is mature.

Optionally, the preset number requirement is that in the statistical results corresponding to the filtered data set, the total number of statistical values in each preset wind speed interval is greater than or equal to the second number, and the number of wave height intervals in each preset wind speed interval is greater than or equal to or equal to the third number, and there are at least two preset wave height intervals that meet the preset number of quantum requirements, and the preset number of quantum requirements is the number of statistical values in the first wind speed interval and the second wind speed interval under a preset wave height interval are greater than or equal to the fourth number, and the total number of statistical values in the preset wave height interval is greater than or equal to the fifth number.

Optionally, according to the statistical results corresponding to the filtered data set, determine whether the lidar system corresponding to the filtered data set is mature, including:

In the statistical results corresponding to the filtered data set, a first linear regression equation is established for the wind speed statistics in each preset wave height interval, and a second linear regression equation is established for the wind speed statistics in all preset wave height intervals, so as to Obtain the slopes and correlation coefficients corresponding to the first linear regression equations respectively, and the slopes and correlation coefficients corresponding to the second linear regression equations;

According to the slopes and correlation coefficients corresponding to the first linear regression equations, and the slopes and correlation coefficients corresponding to the second linear regression equations, it is determined whether the lidar system corresponding to the filtered data set is mature.

Optionally, the statistical value of the wind speed is the average value of the wind speed, and the setting condition further includes at least one height above the ground;

Calculate the uncertainty accuracy level of the target lidar system according to the target filtered data set, including:

For each filtered dataset contained in the target filtered dataset:

Classify the filtered data set according to the height above the ground, and obtain at least one set of statistical values corresponding to the height above the ground;

Determine the final accuracy corresponding to at least one ground clearance under the filtered data set according to the statistical value set corresponding to at least one ground clearance respectively;

To obtain the final precision corresponding to at least one ground clearance under each filtered data set included in the target filtered data set;

The uncertainty accuracy level of the target lidar system is determined according to the final accuracy respectively corresponding to at least one height above the ground under each filtered data set included in the target screened data set.

Optionally, according to the set of statistical values corresponding to at least one height above the ground, determine the final precision corresponding to at least one height above the ground in the filtered data set, including:

Calculate the value and value range of the at least one ground clearance corresponding to the preset environmental factor according to the set of statistical values corresponding to the at least one ground clearance respectively;

The target environmental factor is determined from the preset environmental factors according to the average wind speed included in the set of statistical values corresponding to the at least one height above the ground and the value of the at least one height above the ground corresponding to the preset environmental factor, wherein the target environmental factor Has a significant impact on the uncertainty accuracy level of the target lidar system;

Determine the maximum deviation of the at least one ground clearance corresponding to the target environmental factor according to the slope of the equation and the value range of the at least one ground clearance respectively corresponding to the target environmental factor;

For each of the at least one ground clearance, calculate the initial accuracy corresponding to the ground clearance according to the maximum deviation of the ground clearance corresponding to the target environmental factor, so as to obtain the initial accuracy corresponding to the at least one ground clearance respectively ;

The initial precision corresponding to the at least one ground clearance is divided by the preset value to obtain the final precision corresponding to the at least one ground clearance, which is used as the final precision corresponding to the at least one ground clearance in the filtered data set.

Optionally, the target environmental factor is determined from the preset environmental factors according to the average value of the wind speed contained in the set of statistical values corresponding to the at least one height above the ground, and the value of the at least one height above the ground corresponding to the preset environmental factor, including: :

Calculate the wind speed deviation percentage corresponding to the at least one height from the ground according to the average value of the wind speed included in the set of statistical values corresponding to the at least one height from the ground;

A third linear regression equation is established according to the value of the preset environmental factor corresponding to the at least one height above the ground, and the wind speed deviation percentage corresponding to the at least one height above the ground, so as to obtain the third linear regression equation that the at least one height above the ground corresponds to the preset environmental factor. Trilinear regression equation;

Determine the slope of the equation, the standard deviation of the preset environmental factor, and the correlation coefficient according to the third linear regression equation in which the at least one height above the ground corresponds to the preset environmental factor respectively, as the slope of the equation of the at least one height above the ground corresponding to the preset environmental factor respectively , the standard deviation and correlation coefficient of preset environmental factors;

The target environmental factor is determined from the predetermined environmental factors according to the slope of the equation, the standard deviation of the predetermined environmental factor and the correlation coefficient respectively corresponding to at least one height above the ground.

Optionally, the uncertainty accuracy level of the target lidar system is determined according to the final accuracy corresponding to at least one ground clearance under each filtered data set included in the target filtered data set, including:

Calculate the sum of squares of the final precisions corresponding to at least one height above the ground in the target filtered data set;

Root the sum of squares to get the uncertainty accuracy level of the target lidar system.

A grading device for a lidar system, comprising: a target data set acquisition module, an invalid data elimination module, a capture matrix statistics module, a quantity requirement satisfaction judging module, a radar maturity judging module and an uncertainty calculation module;

The target data set acquisition module is used to acquire the target data set, wherein the target data set includes at least two laser radar systems of the same model and the statistical values of the data collected by the wind towers located in the two sea areas under the set conditions. a data set, the statistical value includes at least the statistical value of wind speed, and the setting condition includes at least one wave height;

The invalid data removal module is used to remove invalid data from the target data set to obtain the target filtered data set;

The capture matrix statistics module is used to perform capture matrix statistics on the target screened data set, and obtain statistical results corresponding to the target screened data set, wherein the capture matrix is used for statistical wave heights within each preset wave height interval and wind speed statistics. Set the number of statistical values in the wind speed interval, as well as the total number of statistical values and the number of wave height intervals in each preset wind speed interval, the number of wave height intervals in a preset wind speed interval means that the number of statistical values in the preset wind speed interval is greater than or equal to The number of preset wave height intervals equal to the first number;

The quantity requirement satisfaction judgment module is used to determine whether the number of statistical values contained in the target filtered data set meets the preset quantity requirement according to the statistical results corresponding to the target filtered data set;

The radar maturity judging module is used to determine whether the target lidar system is in the target lidar system according to the statistical results corresponding to the data set after the target screening, if the quantity requirement is satisfied by the situation judging module. Mature, among which, the target lidar system includes at least two lidar systems of the same model;

The uncertainty calculation module is used to calculate the uncertainty accuracy level of the target lidar system according to the target screening data set if the radar maturity judgment module determines that the target lidar system is mature.

It can be seen from the above technical solutions that the classification method of the lidar system provided by the present application first obtains the target data set, then removes the invalid data in the target data set, obtains the target screening data set, and then performs the target screening data set. Capture matrix statistics to obtain the statistical results corresponding to the target-filtered data set, and then determine whether the number of statistical values contained in the target-filtered data set meets the preset number requirements according to the statistical results corresponding to the target-filtered data set, and if so, according to The statistical results corresponding to the data set after target screening determine whether the target lidar system is mature. If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated according to the target screening data set. It can be seen that the present application can determine whether the number of statistical values contained in the target filtered data set meets the preset number requirement according to the statistical results after the capture matrix statistics are performed on the target-screened data set, and whether the target lidar system is Mature, when the target lidar system is mature, the present application can calculate the uncertainty accuracy level of the target lidar system according to the target filtered data set.

Description of drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only It is an embodiment of the present application. For those of ordinary skill in the art, other drawings can also be obtained according to the provided drawings without any creative effort.

FIG. 1 is a schematic flowchart of a classification method for a lidar system provided by an embodiment of the present application;

Figure 2 is a schematic diagram of a test scene composed of a lidar system and an anemometer tower;

FIG. 3 is a schematic structural diagram of a classification device of a lidar system provided by an embodiment of the present application;

FIG. 4 is a block diagram of a hardware structure of a classification device of a lidar system provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

The present application provides a classification method and apparatus for a laser radar system. Next, the classification method for a laser radar system provided by the present application will be described in detail through the following embodiments.

Please refer to FIG. 1 , which shows a schematic flowchart of a classification method for a laser radar system provided by an embodiment of the present application. The classification method for a laser radar system may include:

Step S101, acquiring a target data set.

Among them, the target data set includes at least two laser radar systems of the same model and three data sets consisting of the statistical values of the data collected by the wind measuring towers located in the two sea areas under the set conditions, and the statistical values include at least the statistical value of the wind speed. The predetermined condition includes at least one wave height.

The embodiments of the present application can collect data under set conditions based on two lidar systems of the same model and anemometer towers located in two sea areas, and perform graded tests on the lidar systems.

Here, sensors such as wind speed, wind direction, temperature and humidity, and air pressure are installed on the wind measuring tower, as well as a wave profile current meter, which is used to collect wave height data. In this step, considering that different lidar systems may have different requirements for water depth and waves, it is necessary to select an appropriate offshore wind tower for comparison and testing according to different types of lidar systems. In order to ensure that the calculated uncertainty accuracy level is more accurate, this step requires at least two offshore wind measuring towers, and the weather and wave conditions in the sea area where the two offshore wind measuring towers are located are preferably different, so as to better The effects of lidar systems under these conditions were tested.

Optionally, the lidar system may specifically be a floating lidar system; in this step, at least two lidar systems of the same model are required, wherein the two lidar systems are graded and tested in the same sea area, and the two lidar systems are tested in the same sea area. One of the lidar systems needs to be graded again in another sea area. Taking the floating lidar system as an example, as shown in Figure 2, the floating radar system 1 and the floating radar system 2 collect data in the test sea area 1, and the floating radar system 1 also collects data in the test sea area 2.

In this embodiment, the data storage requirements of the lidar system and the wind measuring tower are statistical values within a set period of time, that is, for the laser radar system and the wind measuring tower, after the data is collected, the The timer counts the data collected within the set duration, obtains the statistic value within the set duration, and stores the statistic value. Optionally, the set duration is 10 minutes, and the statistical values include but are not limited to: maximum value, minimum value, standard deviation, and statistical value.

In this step, the statistical values of the data collected by the anemometer towers located in the same sea area and a lidar system form a data set. Therefore, the statistics of the data collected by the two lidar systems of the same model and the anemometer towers located in the two sea areas will form a data set. The values make up three data sets. For example, for Figure 2, the statistical values of the data collected by the floating radar system 1 and the wind tower located in the test sea area 1 form the first data set. The statistical values of the data collected by the wind tower in sea area 1 form the second data set, and the statistical values of the data collected by the floating radar system 1 and the wind tower located in the test sea area 2 form the third data set; then, in this step, the obtained The target data set includes at least the three data sets, that is, the classification test is performed based on at least the three data sets, which can make the uncertainty accuracy level finally calculated in this embodiment more accurate.

It is worth noting that the time error of the collectors of the lidar system and the wind measuring tower in this embodiment must be within 6 seconds, otherwise, the calculated uncertainty accuracy level may also be inaccurate. Based on this, the collector can be calibrated once a week, so that the collector time error of the lidar system and the wind tower can always be kept within 6 seconds.

It should also be noted that the above-mentioned data collected by the lidar system and the wind measuring tower is carried out under set conditions. Optionally, the set conditions include at least one wave height, that is, the data collected by the laser radar system and the wind measuring tower. Data refers to data corresponding to at least one wave height.

In addition, optionally, the data collected by the lidar system and the wind measuring tower may include wind speed data, then the above statistical value specifically refers to the wind speed statistical value; of course, the data collected by the laser radar system and the wind measuring tower may also include other data, For example, wind direction, temperature, humidity, etc., are not limited in this application.

Step S102: Eliminate invalid data in the target data set to obtain the target filtered data set.

It is understandable that there may be some invalid data in the statistical values of the data collected by the lidar system and the wind measurement tower. In order to avoid invalid data affecting the calculated uncertainty accuracy level, invalid data needs to be eliminated.

Optionally, the invalid data refers to the following data: first, the data in the sector affected by surrounding obstacles; second, the reference anemometer is affected by the wind measuring tower, the support and other equipment; third, the laser The data when the radar system or the offshore wind tower instrument is damaged; fourth, the data when the conditions such as waves exceed the allowable range of the lidar system.

Step S103: Perform capture matrix statistics on the target filtered data set to obtain statistical results corresponding to the target filtered data set.

First, the capture matrix is introduced.

In this step, the capture matrix can count the number of statistical values included in each filtered data set according to the preset wind speed interval and the preset wave height interval. The number of statistical values whose statistical values are in each preset wind speed interval, and the total number of statistical values and the number of wave height intervals in each preset wind speed interval. The number of wave height intervals in a preset wind speed interval refers to the statistics in the preset wind speed interval. The number of values is greater than or equal to the first number of preset wave height intervals.

It should be noted that the present application does not limit the first number, which may be determined according to the actual situation. For example, the first number may be set to 3.

In order to facilitate understanding of the capture matrix, a capture matrix is exemplarily given below. It should be noted that each preset wind speed interval and preset wave height interval included in the capture matrix shown in Table 1 are only examples, and are not intended to limit the present application.

Table 1 Capture matrix statistics

As described in the preceding steps, the target filtered data set includes at least three data sets, then the target filtered data set in this step includes the filtered data sets corresponding to the at least three data sets respectively. Performing capture matrix statistics on the target filtered data set” is actually to perform capture matrix statistics on each filtered data set included in the target filtered data set, that is, the process of this step includes: For each screened data set, capture matrix statistics are performed on the screened data set to obtain statistical results corresponding to the screened data set; to obtain the respective statistical results corresponding to each screened data set included in the target screened data set.

Step S104 , according to the statistical results corresponding to the target filtered data set, determine whether the number of statistical values contained in the target filtered data set meets the preset number requirement.

In this embodiment, one of the functions of the capture matrix is to judge whether the number of statistical values contained in the target-screened data set is sufficient for the grading test. Based on this, in this step, the target screening can be determined according to the statistical results corresponding to the target-screened data set Whether the number of statistical values contained in the post data set meets the preset number requirement.

It has been described above that "the target filtered data set includes at least three filtered data sets corresponding to the respective filtered data sets", the process of this step may include: for each filtered data set included in the target filtered data set, according to The statistical result corresponding to the filtered data set determines whether the number of statistical values contained in the filtered data set meets the preset number requirement.

Optionally, the preset number requirement may be: in the statistical result corresponding to the filtered data set, the total number of statistical values in each preset wind speed interval is greater than or equal to the second number, and the wave height interval in each preset wind speed interval The number is greater than or equal to the third number, and there are at least two preset wave height intervals that meet the preset number of quantum requirements, and the preset number of quantum requirements is the statistical value in the first wind speed interval and the second wind speed interval under a preset wave height interval The numbers are all greater than or equal to the fourth number, and the total number of statistical values in the preset wave height interval is greater than or equal to the fifth number.

The above Table 1 is taken as an example to illustrate the preset quantity requirement.

If in Table 1, each value contained in the row of the total number of statistical values is greater than or equal to the second quantity, and each value contained in the row of the number of wave height intervals is greater than or equal to the third quantity, and there are at least two predicted Assuming that the wave height interval meets the preset quantity requirements, the number of statistical values included in the filtered data set corresponding to Table 1 meets the preset quantity requirements. Wherein, for the preset number of quantum requirements, if the number of statistical values in the first wind speed interval under a preset wave height interval is greater than or equal to the fourth number, and the number of statistical values in the second wind speed interval under the preset wave height interval If the number is greater than or equal to the fourth number, and the total number of statistical values in the preset wave height interval is greater than or equal to the fifth number, then the preset wave height interval meets the preset number sub-requirements.

Here, the number of statistical values in the first wind speed interval under a preset wave height interval refers to the sum of the values in the row of the preset wave height interval in the first wind speed interval, and the statistics in the second wind speed interval under a preset wave height interval The number of values refers to the sum of the values in the second wind speed interval in the row of the preset wave height interval, and the total number of statistical values in a preset wave height interval refers to the sum of all the values in the row of the preset wave height interval.

It should be noted that the above-mentioned second quantity, third quantity, fourth quantity and fifth quantity can all be determined according to actual conditions, which are not limited in this application. For example, the second quantity can be 10, and the third quantity can be 2, the fourth number can be 36, and the fifth number can be 144; the sum of the first wind speed interval and the second wind speed interval is equal to the sum of all preset wind speed intervals, for example, for Table 1, the first wind speed interval is refers to [4,8), and the second wind speed interval refers to [8,16.5).

Step S105: If satisfied, determine whether the target lidar system is mature according to the statistical results corresponding to the data set after target screening.

Among them, the target lidar system includes at least two lidar systems of the same type.

In this embodiment, another function of the capture matrix is to judge whether the target lidar system is mature enough for a grading test.

Optionally, for each filtered data set included in the target filtered data set, when it is determined in the previous step that the number of statistical values contained in the filtered data set meets the preset number requirement, the data set corresponding to the filtered data set can be determined according to the Statistical results are used to determine whether the lidar system corresponding to the filtered data set is mature. This judgment process is performed for each filtered data set, that is, it can be obtained whether the laser radar system corresponding to each filtered data set included in the target filtered data set is mature.

In this step, if the respective laser radar systems corresponding to each filtered data set included in the target screened data set are mature, it is determined that the target laser radar system is mature.

For example, with respect to FIG. 2, according to the statistical results corresponding to the filtered data set corresponding to the "first data set" mentioned in step S101, it is determined that the floating radar system 1 is mature, and according to the "first data set" mentioned in step S101 The statistical result corresponding to the filtered data set corresponding to the second data set” determines that the floating radar system 2 is mature, and the statistics corresponding to the filtered data set corresponding to the “third data set” mentioned in step S101 As a result, if it is determined that the floating radar system 1 is mature, it is determined that both the floating radar systems 1 and 2 are mature; if according to the statistical result corresponding to the filtered data set corresponding to the "first data set" mentioned in step S101, it is determined that the floating radar system 1 is mature. The floating radar system 1 is mature. According to the statistical results corresponding to the filtered data set corresponding to the "third data set" mentioned in step S101, it is determined that the floating radar system 1 is immature, and the floating radar system 1 is determined to be immature.

Optionally, in this step, when it is determined that a certain lidar system included in the target lidar system is immature, the data set after target screening and the above judgment process may also be analyzed to further analyze whether the lidar system is really immature. , if further analysis finds that the lidar system is mature, the target lidar system can still be considered mature; if further analysis finds that the lidar system is indeed immature, the target lidar system is considered immature.

Step S106 , if the target lidar system is mature, calculate the uncertainty accuracy level of the target lidar system according to the target filtered data set.

In this step, the classification test can be carried out when the target lidar system is mature. If the target lidar system is immature, even if the uncertainty accuracy level of the target lidar system can be calculated according to the target-screened data set, the calculation The uncertainty accuracy level of the target lidar system is also not accurate.

The classification method of the lidar system provided by the present application firstly obtains the target data set, then removes the invalid data in the target data set to obtain the target screening data set, and then performs the capture matrix statistics on the target screening data set to obtain the target screening Then, according to the statistical results corresponding to the target-filtered data set, it is determined whether the number of statistical values contained in the target-filtered data set meets the preset number requirement. Statistical results are used to determine whether the target lidar system is mature. If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated according to the target screening data set. It can be seen that the present application can determine whether the number of statistical values contained in the target filtered data set meets the preset number requirement according to the statistical results after the capture matrix statistics are performed on the target-screened data set, and whether the target lidar system is Mature, when the target lidar system is mature, the present application can calculate the uncertainty accuracy level of the target lidar system according to the target filtered data set.

In an embodiment of the present application, considering that when removing invalid data in step S102, if a lot of invalid data is removed, for example, 4 out of 10 statistical values are invalid data, it means that the maturity of the lidar system needs to be improved. The classification test is not carried out, and the classification test needs to be carried out after the lidar system is sufficiently mature. That is to say, in this embodiment, it is necessary to determine the data validity according to the target screening data set and the target data set, and then determine whether the target lidar system is mature according to the data validity. If the target lidar system is mature, perform the above steps S103, if the target lidar system is immature, step S103 and subsequent steps are not executed.

Optionally, the process of "determining the data efficiency according to the target filtered data set and the target data set" may include: for each filtered data set included in the target filtered data set and the corresponding data set in the target data set, The number of statistical values contained in the filtered data set is divided by the number of statistical values contained in the corresponding data set, and the obtained quotient is the data efficiency corresponding to the filtered data set.

Correspondingly, the process of "determining whether the target lidar system is mature according to the data efficiency" may include: for each filtered data set included in the target filtered data set, if the data efficiency corresponding to the filtered data set is greater than or is equal to the preset effective rate threshold, it is determined that the lidar system corresponding to the filtered data set is mature; otherwise, it is determined that the lidar system corresponding to the filtered data set is immature; if the target filtered data set contains each filtered data set If the lidar systems corresponding to the set are mature, the target lidar system is determined to be mature.

Optionally, the above-mentioned preset effective rate threshold may be 95%. Of course, the preset effective rate threshold may also be set to other values according to the actual situation, which is not limited in this application.

In this embodiment, after removing invalid data, first determine whether the target lidar system is mature according to the data efficiency.

In an embodiment of the present application, the process of "judging whether the lidar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set" mentioned in the above step S105 is introduced.

Optionally, the process of "judging whether the lidar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set" may include:

A1. In the statistical results corresponding to the filtered data set, a first linear regression equation is established for the wind speed statistics in each preset wave height interval, and a second linear regression equation is established for the wind speed statistics in all preset wave height intervals. , so as to obtain the slopes and correlation coefficients corresponding to the first linear regression equations respectively, and the slopes and correlation coefficients corresponding to the second linear regression equations.

Take Table 1 as an example for description.

First, in this step, a first linear regression equation can be established according to each wind speed statistical value in the row whose preset wave height interval is "<1", and according to each wind speed statistical value in the row whose preset wave height interval is "[1,2)" Establish a first linear regression equation, ..., and so on, establish a first linear regression equation according to each wind speed statistical value of the row whose preset wave height interval is ">7", thus, a total of 8 first linear regression equations are established. regression equation.

Then, in this step, a second linear regression equation can be established according to the statistical values of the wind speeds in 8 rows in which the preset wave height interval is "<1" to ">7".

Finally, based on the above-established 8 first linear regression equations and 1 second linear regression equation, the regression analysis is carried out respectively, and the corresponding slopes and correlation coefficients of the 8 first linear regression equations and the 1 second linear regression equation can be obtained respectively. (ie R ² ).

It should be noted that the formats of the first linear regression equation and the second linear regression equation are both y=kx+b, where x is the wind speed statistical value of the wind speed collected by the lidar system, and y is the wind speed collected by the wind measuring tower. Statistics.

A2. Determine whether the lidar system corresponding to the filtered data set is mature according to the respective slopes and correlation coefficients of the first linear regression equations, and the corresponding slopes and correlation coefficients of the second linear regression equations.

Optionally, if the slopes corresponding to the first linear regression equations and the slopes corresponding to the second linear regression equations are both within the first preset slope range, and the correlation coefficients corresponding to the first linear regression equations and the second linear regression equations are both within the range of the first preset slope. If the correlation coefficients corresponding to the linear regression equation are all greater than or equal to the preset correlation coefficient threshold, it is determined that the lidar system corresponding to the filtered data set is mature.

Optionally, the above process of “judging whether the lidar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set” not only determines whether the lidar system is mature based on the statistical value of wind speed, but also needs to be based on the wind direction. To make a judgment, that is, to judge whether the lidar system is mature based on the statistical value of wind speed and wind direction at the same time, this step also needs to meet the following conditions on the basis of the above conditions: the first linear regression equations established based on the wind direction (for the specific establishment process, please refer to the statistics based on wind speed). value establishment process) corresponding slopes respectively, and the slopes corresponding to the second linear regression equation established based on the wind direction (for the specific establishment process, please refer to the establishment process based on the wind speed statistical value), the corresponding slopes are all within the second preset slope range, and, The correlation coefficients corresponding to the first linear regression equations established based on the wind direction, and the correlation coefficients corresponding to the second linear regression equations established based on the wind direction are all greater than or equal to the preset correlation coefficient threshold. Only then can the lidar system be determined to be mature . Otherwise, it is believed that the maturity of the lidar system needs to be improved, and it is not recommended to carry out grading testing at this stage.

It should be noted that this application does not limit the above-mentioned first preset slope range, second preset slope range and preset correlation coefficient threshold, which can be determined according to actual conditions. For example, the above-mentioned first preset slope range can be 0.98 ~1.02, the second preset slope range may be 0.95-1.05, and the preset correlation coefficient threshold may be 0.98.

This embodiment can determine whether the lidar system corresponding to the filtered data set is mature based on the statistical results of the capture matrix, and if not, the subsequent steps are not performed, which further improves the efficiency of the classification test.

The following embodiments describe the above-mentioned "step S106, calculating the uncertainty accuracy level of the target lidar system according to the filtered data set of the target".

Optionally, the above-mentioned statistical value of the wind speed is the average value of the wind speed, and the setting condition may also include at least one height above the ground. Based on this, the above-mentioned "step S106: Calculate the uncertainty accuracy of the target lidar system according to the target filtered data set. Level" process can include B1~B2:

B1. Each screened data set included in the target screened data set: classify the screened data set according to the height above the ground, and obtain at least one set of statistical values corresponding to the ground clearance; Respectively corresponding statistical value sets, determine the final accuracy corresponding to at least one ground clearance under the filtered data set; to obtain the final accuracy corresponding to at least one ground clearance under each filtered data set included in the target filtered data set. precision.

In the grading test, the lidar system and the reference sensor (that is, the sensor installed on the wind tower) need to calculate the final accuracy at the same height. Therefore, for each filtered data set included in the target filtered data set, in this step, it is necessary to first classify the filtered data set according to the ground clearance to obtain at least one set of statistical values corresponding to the ground clearance, and then According to the obtained statistical value sets corresponding to at least one height above the ground, the final accuracy is calculated respectively.

Optionally, in this step, when "determining the final accuracy corresponding to at least one ground clearance under the filtered data set according to the statistical value set corresponding to at least one ground clearance respectively", the specific process may include B11 to B15:

B11. Calculate the value and value range of the at least one ground clearance corresponding to the preset environmental factor respectively according to the set of statistical values corresponding to the at least one ground clearance respectively.

At present, the known environmental variables that affect the lidar system include: wind shear, inflow angle and wind steering. In order to improve the accuracy of the uncertainty accuracy level calculated in this application, wave height, turbulence intensity, precipitation , wind direction, air temperature, air density, temperature difference between two different heights, cloudiness and other environmental factors are analyzed. Based on this, the "preset environmental factors" in this step can be one of the environmental factors mentioned above or variety.

It can be understood that the value of each environmental factor included in the preset environmental factor can be determined according to the set of statistical values corresponding to the corresponding height above the ground, that is, for each height above the ground, this step can be based on the corresponding height above the ground. Calculate the value of the height from the ground corresponding to the preset environmental factor, where the value of the height from the ground corresponding to the preset environmental factor refers to the preset environment determined according to the set of statistical values corresponding to the height from the ground the value of the factor.

After the values of the at least one ground clearance corresponding to the preset environmental factors are determined, it is also possible to determine the value ranges of the at least one ground clearance corresponding to the preset environmental factors.

B12. Determine the target environmental factor from the preset environmental factors according to the average value of the wind speed included in the set of statistical values corresponding to the at least one height above the ground and the value of the at least one height above the ground corresponding to the preset environmental factor, wherein the target Environmental factors have a significant impact on the uncertainty accuracy level of a target lidar system.

In this step, an environmental factor that has a significant impact on the calculation of the uncertainty accuracy level needs to be determined from the preset environmental factors as the target environmental factor.

Optionally, after determining the "environmental factors with significant influence", if there is a correlation between the determined environmental factors, for example, the calculation of the uncertainty accuracy level of both environmental factors A and B has a significant influence, and A and B have a significant influence. If there is a correlation between B, it is necessary to consider whether the influence of A on the uncertainty accuracy level is caused by B, and if so, A is not included in the target environmental factors; similarly, if the influence of B on the uncertainty accuracy level is Due to A, B is not included in the target environmental factor. Based on this, after determining the "environmental factors with significant influence", only the environmental variables that directly affect the uncertainty accuracy level are left, and the environmental variables that do not directly affect the uncertainty accuracy level are excluded to obtain the target environment. factor.

In an optional embodiment, the specific implementation process of this step may include the following B121-B123:

B121. Calculate the wind speed deviation percentage corresponding to the at least one height from the ground according to the average value of the wind speed included in the set of statistical values corresponding to the at least one height from the ground.

It can be understood that the average value of wind speed included in the set of statistical values corresponding to a height above the ground includes the average value of wind speed corresponding to the wind speed collected by the lidar system and the average value of wind speed corresponding to the wind speed collected by the wind tower. At the height, the lidar system collects the average value of the wind speed corresponding to the wind speed and the average value of the wind speed corresponding to the wind speed collected by the wind measuring tower, and calculates the percentage of wind speed deviation corresponding to the height above the ground.

Optionally, for each of the at least one height above the ground, the calculation formula of the wind speed deviation percentage corresponding to the height above the ground is:

Among them, v _RSD refers to the average wind speed corresponding to the wind speed collected by the lidar system, and v _reference refers to the average wind speed corresponding to the wind speed collected by the wind tower.

B122. Establish a third linear regression equation according to the value of the preset environmental factor corresponding to the at least one height above the ground and the wind speed deviation percentage corresponding to the at least one height from the ground, so as to obtain that the at least one height above the ground corresponds to the preset environmental factor respectively The third linear regression equation of .

In this step, for each of the at least one height above the ground, the percentage of wind speed deviation corresponding to the height above the ground may be used as the dependent variable, and the value of the preset environmental factor corresponding to the height above the ground may be used as Independent variables, establish a one-dimensional, two-parameter third linear regression equation according to the independent variables and dependent variables.

B123. Determine the slope of the equation, the standard deviation of the preset environmental factor, and the correlation coefficient according to the third linear regression equation in which the at least one height above the ground corresponds to the preset environmental factor, respectively, as the at least one height above the ground corresponding to the preset environmental factor. Equation slopes, standard deviations for preset environmental factors, and correlation coefficients.

For each of the at least one height above the ground, in this step, regression analysis may be performed based on the third linear regression equation in which the height above the ground corresponds to the preset environmental factor, to obtain the slope of the equation (represented by m), the preset Standard deviation (represented by std) and correlation coefficient (represented by R2 ⁾ of environmental factors, of course, regression analysis can also be performed to calculate deviation (represented by C) and the average value of preset environmental factors (represented by avg).

B124. Determine the target environmental factor from the predetermined environmental factors according to the slope of the equation, the standard deviation of the predetermined environmental factor, and the correlation coefficient, respectively corresponding to the at least one height above the ground.

Specifically, for each of the at least one ground clearance, this step may first calculate the ground clearance according to the slope m of the equation corresponding to the predetermined environmental factor and the standard deviation std of the predetermined environmental factor. The height corresponds to the sensitivity of the preset environmental factor; and then the target environmental factor is determined from the preset environmental factors according to the sensitivity and correlation coefficient of at least one height above the ground corresponding to the preset environmental factor.

See Table 2 below for a clearer understanding of the relationship between ground clearance, preset environmental factors (ie, independent variables), and parameters, sensitivities, etc. calculated through regression analysis.

Table 2 Statistical table of parameters and sensitivity calculated by regression analysis

Optionally, the slope m of the equation in which the height above the ground corresponds to the preset environmental factor may be multiplied by the standard deviation std of the preset environmental factor, and the product is the sensitivity of the height above the ground corresponding to the preset environmental factor.

Optionally, the process of “determining the target environmental factor from the preset environmental factor according to the sensitivity and correlation coefficient of at least one height above the ground corresponding to the preset environmental factor” may include: for each environment included in the preset environmental factor factor, as long as there is a height above the ground that satisfies the first condition or the second condition, the environmental factor is taken as the target environmental factor. Here, the first condition is: the sensitivity of the height above the ground corresponding to the environmental factor is greater than or equal to the sensitivity threshold, and the second condition is: the height above the ground corresponds to the sensitivity of the environmental factor and R (ie, the square root of the correlation coefficient) The product of is greater than or equal to the set product threshold. Optionally, the above-mentioned sensitivity threshold may be 0.5, and the above-mentioned set product threshold may be 0.1.

B13. Determine the maximum deviation of the at least one ground clearance corresponding to the target environmental factor according to the slope of the equation and the value range of the at least one ground clearance corresponding to the target environmental factor respectively.

Optionally, for each of the at least one ground clearance, the slope of the equation corresponding to the ground clearance respectively corresponding to the target environmental factor is denoted as m, and the ground clearance corresponds to the value range of the target environmental factor respectively. Denoted as range, the maximum deviation of the height from the ground corresponding to the target environmental factor is m*range.

In this step, the slope of the equation, the value range and the maximum deviation of the at least one height above the ground corresponding to the target environmental factors can be counted, and the following Table 3 can be obtained (with the target environmental factors including wind shear index, inflow angle, vertical wind direction variation and wave height as examples).

Table 3 Statistical table of equation slope, value range and maximum deviation of target environmental factors

B14. For each of the at least one ground clearance, according to the maximum deviation of the ground clearance corresponding to the target environmental factor, calculate the initial accuracy corresponding to the ground clearance to obtain at least one ground clearance corresponding to the initial precision.

Optionally, for each of the at least one height from the ground, the square and the square of the maximum deviation of the height from the ground corresponding to the target environmental factor may be used as the initial accuracy corresponding to the height from the ground. For example, the height m1 corresponds to the wind shear index, the inflow angle, the vertical wind direction change and the maximum deviation of the wave height are a, b, c and d respectively, then the initial accuracy corresponding to the height m1 is:

B15. Divide the initial precision corresponding to the at least one ground clearance by the preset value to obtain the final precision corresponding to the at least one ground clearance, which is used as the final precision corresponding to the at least one ground clearance in the filtered data set.

则对于至少一个离地高度中的每个离地高度，均可将该离地高度对应的初始精度除以

得到该离地高度对应的最终精度。In this step, the preset value can be

then for each of the at least one ground clearance, the initial accuracy corresponding to the ground clearance can be divided by

Get the final accuracy corresponding to the height above the ground.

It is worth noting that each filtered data set included in the target filtered data set can be calculated according to the above steps B11 to B15, so that at least one ground clearance corresponding to each filtered data set can be obtained. final accuracy.

For example, if the target filtered data set includes 4 filtered data sets, and at least one of the heights above the ground is the heights m1, m2, and m3, then through the calculation of B1, a total of 12 final accuracies can be obtained.

B2. Determine the uncertainty accuracy level of the target lidar system according to the final accuracy respectively corresponding to at least one height above the ground under each filtered data set included in the target screened data set.

Optionally, this step may specifically include the following steps: calculating the sum of squares of the final accuracy corresponding to at least one height above the ground in the target-screened data set, and taking the square root of the sum of squares to obtain the uncertainty of the target lidar system. Accuracy class.

For example, as in the previous example, if the target filtered data set includes 4 filtered data sets, and at least one of the heights above the ground is m1, m2, and m3, then 12 final accuracies can be obtained, and in this step, the target lidar can be obtained. The uncertainty accuracy level of the system refers to the squared sum of the 12 final accuracies and then the square root.

To sum up, the embodiments of the present application can calculate the uncertainty accuracy level of the target lidar system. It is worth noting that this uncertainty accuracy level can only represent the uncertainty accuracy level of the same type of lidar system of the target lidar system. If you need to determine the uncertainty accuracy level of other types of lidar systems, you can follow this The steps provided in the application embodiments are calculated to obtain the uncertainty accuracy levels of other types of lidar systems.

An embodiment of the present application further provides a classification device for a lidar system. The classification device for a lidar system provided by an embodiment of the present application is described below. The grading methods can be referred to each other correspondingly.

Please refer to FIG. 3 , which shows a schematic structural diagram of a grading apparatus of a lidar system provided by an embodiment of the present application. As shown in FIG. 3 , the grading apparatus of a lidar system may include: a target data set acquisition module 301 , an invalid data rejection Module 302 , a capture matrix statistics module 303 , a quantity requirement satisfaction condition judgment module 304 , a radar maturity judgment module 305 and an uncertainty calculation module 306 .

A target data set acquisition module 301 is used to acquire a target data set, wherein the target data set at least includes two laser radar systems of the same model and statistical values of data collected by anemometer towers located in two sea areas under set conditions. Three data sets, the statistical value includes at least the statistical value of wind speed, and the set condition includes at least one wave height.

The invalid data removal module 302 is used for removing invalid data in the target data set to obtain the target filtered data set.

The capture matrix statistics module 303 is configured to perform capture matrix statistics on the target screened data set, and obtain statistical results corresponding to the target screened data set, wherein the capture matrix is used to count that the wave height is in each preset wave height interval and the wind speed statistical value is in each preset wave height interval. The number of statistical values in the preset wind speed interval, and the total number of statistical values and the number of wave height intervals in each preset wind speed interval. The number of wave height intervals in a preset wind speed interval means that the number of statistical values in the preset wind speed interval is greater than or equal to the first number of preset wave height intervals.

The quantity requirement satisfaction judging module 304 is configured to determine whether the quantity of statistical values contained in the target filtered data set meets the preset quantity requirement according to the statistical result corresponding to the target filtered data set.

The radar maturity judging module 305 is configured to determine the target lidar system according to the statistical results corresponding to the data set after the target screening according to the statistical results corresponding to the data set after the target screening, if the quantity requirement meets the situation judging module determines that the number of statistical values contained in the target screening data set meets the preset quantity requirement Whether it is mature, among them, the target lidar system includes at least two lidar systems of the same model.

The uncertainty calculation module 306 is configured to calculate the uncertainty accuracy level of the target lidar system according to the target-screened data set if the radar maturity judgment module determines that the target lidar system is mature.

The classification device of the lidar system provided by the present application first obtains the target data set, then removes the invalid data in the target data set to obtain the target screening data set, and then performs the capture matrix statistics on the target screening data set to obtain the target screening Then, according to the statistical results corresponding to the target-filtered data set, it is determined whether the number of statistical values contained in the target-filtered data set meets the preset number requirement. Statistical results are used to determine whether the target lidar system is mature. If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated according to the target screening data set. It can be seen that the present application can determine whether the number of statistical values contained in the target filtered data set meets the preset number requirement according to the statistical results after the capture matrix statistics are performed on the target-screened data set, and whether the target lidar system is Mature, when the target lidar system is mature, the present application can calculate the uncertainty accuracy level of the target lidar system according to the target filtered data set.

In a possible implementation manner, the grading apparatus of the lidar system provided by the present application may further include: an effective rate calculation module and an effective rate reference module.

Among them, the effective rate calculation module is used to determine the data effective rate according to the target filtered data set and the target data set.

The efficiency reference module is used to determine whether the target lidar system is mature according to the data efficiency, so that when the target lidar system is mature, the capture matrix statistics of the target screening data set are performed, and the statistics corresponding to the target screening data set are obtained. result.

In a possible implementation manner, the above-mentioned target filtered data set includes at least three filtered data sets corresponding to each of the three data sets.

Based on this, the capture matrix statistics module 303 can be specifically configured to perform capture matrix statistics for each screened data set included in the target screened data set, and obtain statistical results corresponding to the screened data set; The statistical results corresponding to each filtered data set included in the target filtered data set are obtained.

Quantity requirement satisfaction judgment module 304 can be specifically used for each filtered data set included in the target filtered data set, and according to the corresponding statistical result of the filtered data set, determine whether the number of statistical values contained in the filtered data set is satisfactory. Preset quantity requirements.

The radar maturity judging module 305 can specifically be used to determine whether the laser radar system corresponding to the filtered data set is mature according to the statistical results corresponding to the filtered data set for each screened data set included in the target screened data set, In order to obtain whether the lidar system corresponding to each filtered data set included in the target-screened data set is mature, if the corresponding lidar system of each filtered data set included in the target-screened data set is mature, the target is determined. Lidar systems are mature.

In a possible implementation manner, the above-mentioned preset number requirement is that in the statistical results corresponding to the filtered data set, the total number of statistical values in each preset wind speed interval is greater than or equal to the second number, and each preset wind speed interval The number of wave height intervals is greater than or equal to the third number, and there are at least two preset wave height intervals that meet the preset number of quantum requirements, and the preset number of quantum requirements is that a preset wave height interval is in the first wind speed interval and the second wind speed The number of statistical values in the interval is greater than or equal to the fourth number, and the total number of statistical values in the preset wave height interval is greater than or equal to the fifth number.

In a possible implementation manner, when the above-mentioned radar maturity judgment module 305 determines whether the lidar system corresponding to the filtered data set is mature according to the statistical result corresponding to the filtered data set, it may include: establishing the first equation Sub-module and radar maturity judgment sub-module.

Among them, the first equation establishment sub-module is used to establish a first linear regression equation for the wind speed statistical values in each preset wave height interval in the statistical results corresponding to the filtered data set, and for the wind speed statistical values in all preset wave height intervals. A second linear regression equation is established based on the statistical value of the wind speed, so as to obtain respective slopes and correlation coefficients corresponding to the first linear regression equations, and slopes and correlation coefficients corresponding to the second linear regression equations.

The radar maturity judgment sub-module is used to determine whether the laser radar system corresponding to the filtered data set corresponds to the respective slopes and correlation coefficients of the first linear regression equations, and the slopes and correlation coefficients corresponding to the second linear regression equations. Mature.

In a possible implementation manner, the above-mentioned statistical value of the wind speed is an average value of the wind speed, and the setting condition further includes at least one height above the ground. Then the above-mentioned uncertainty calculation module 306 may include: a final accuracy calculation sub-module and an uncertainty calculation sub-module.

Among them, the final precision calculation sub-module is used to classify each filtered data set included in the target filtered data set according to the ground clearance, and obtain the statistical value corresponding to at least one ground clearance respectively. Set, according to the set of statistical values corresponding to at least one height above the ground, determine the final precision corresponding to at least one height above the ground in the filtered data set, so as to obtain the minimum accuracy of each filtered data set included in the target filtered data set. The final accuracy corresponding to a height above the ground, respectively.

The uncertainty calculation sub-module is used to determine the uncertainty accuracy level of the target lidar system according to the final accuracy corresponding to at least one height above the ground under each screened data set included in the target screened data set.

In a possible implementation manner, when determining the final accuracy corresponding to at least one ground clearance under the filtered data set according to the statistical value set corresponding to at least one ground clearance respectively, the above-mentioned final precision calculation sub-module may include: A first calculation sub-module, a target environmental factor determination sub-module, a second calculation sub-module, a third calculation sub-module and a fourth calculation sub-module.

Wherein, the first calculation sub-module is configured to calculate the value and value range of the at least one height from the ground corresponding to the preset environmental factor respectively according to the set of statistical values corresponding to the at least one height from the ground.

The target environmental factor determination submodule is configured to determine from the preset environmental factors according to the average wind speed included in the set of statistical values corresponding to the at least one height above the ground and the value of the at least one height above the ground respectively corresponding to the preset environmental factor Target environmental factors, which have a significant impact on the uncertainty accuracy level of the target lidar system.

The second calculation submodule is configured to determine the maximum deviation of the at least one ground clearance corresponding to the target environmental factor according to the slope of the equation and the value range of the at least one ground clearance corresponding to the target environmental factor respectively.

The third calculation submodule is configured to, for each of the at least one ground clearance, calculate the initial accuracy corresponding to the ground clearance according to the maximum deviation of the ground clearance corresponding to the target environmental factor, so as to obtain at least one The initial accuracy corresponding to the height above the ground.

The fourth calculation sub-module is used to divide the initial accuracy corresponding to the at least one height above the ground by the preset value to obtain the final accuracy corresponding to the at least one height above the ground, which is used as the at least one height above the ground in the filtered data set. The corresponding final precision.

In a possible implementation manner, the above-mentioned target environmental factor determination submodule may include: a wind speed deviation calculation submodule, a second equation establishment submodule, a target parameter determination submodule, and a target parameter reference submodule.

The wind speed deviation calculation sub-module is used to calculate the wind speed deviation percentage corresponding to the at least one height above the ground according to the average value of the wind speed included in the set of statistical values corresponding to the at least one height above the ground.

The second equation establishment sub-module is configured to establish a third linear regression equation according to the value of the preset environmental factor corresponding to the at least one height above the ground and the wind speed deviation percentage corresponding to the at least one height above the ground, so as to obtain the at least one height above the ground The third linear regression equations respectively correspond to the preset environmental factors.

The target parameter determination sub-module is configured to determine the slope of the equation, the standard deviation of the preset environmental factor and the correlation coefficient according to the third linear regression equation in which the at least one height above the ground corresponds to the preset environmental factor respectively, as the at least one height above the ground corresponding to The slope of the equation, the standard deviation of the predetermined environmental factor, and the correlation coefficient for the predetermined environmental factor.

The target parameter reference sub-module is configured to determine the target environmental factor from the predetermined environmental factors according to the slope of the equation, the standard deviation of the predetermined environmental factor and the correlation coefficient of at least one height above the ground corresponding to the predetermined environmental factor respectively.

In a possible implementation manner, the above-mentioned uncertainty calculation sub-module may include: a sum of squares calculation module and a square root module.

Wherein, the sum of squares calculation module is used to calculate the sum of squares of the final precisions corresponding to at least one height above the ground under the target screened data set respectively.

The square root module is used to square the sum of squares to obtain the uncertainty accuracy level of the target lidar system.

The embodiments of the present application also provide a classification device for a lidar system. Optionally, FIG. 4 shows a block diagram of the hardware structure of the grading device of the lidar system. Referring to FIG. 4 , the hardware structure of the grading device of the lidar system may include: at least one processor 401, at least one communication interface 402, at least one a memory 403 and at least one communication bus 404;

In the embodiment of the present application, the number of the processor 401, the communication interface 402, the memory 403, and the communication bus 404 is at least one, and the processor 401, the communication interface 402, and the memory 403 complete the communication with each other through the communication bus 404;

The processor 401 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention, etc.;

The memory 403 may include high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), for example, at least one disk memory;

Wherein, the memory 403 stores a program, and the processor 401 can call the program stored in the memory 403, and the program is used for:

Obtain a target data set, wherein the target data set includes at least three data sets consisting of statistical values of data collected by two lidar systems of the same model and anemometer towers located in two sea areas under set conditions, and the statistical values at least include Wind speed statistics, setting conditions include at least one wave height;

Eliminate invalid data in the target data set to obtain the target filtered data set;

Perform capture matrix statistics on the target-screened data set to obtain statistical results corresponding to the target-screened data set, wherein the capture matrix is used to count the number of statistic values whose wave heights are in each preset wave height interval and the wind speed statistical value is in each preset wind speed interval. and the total number of statistical values and the number of wave height intervals in each preset wind speed interval, the number of wave height intervals in a preset wind speed interval refers to the preset wind speed interval whose number of statistical values is greater than or equal to the first number The number of wave height intervals;

According to the statistical results corresponding to the target-filtered data set, determine whether the number of statistical values contained in the target-filtered data set meets the preset number requirement;

If satisfied, determine whether the target lidar system is mature according to the statistical results corresponding to the data set after target screening, wherein the target lidar system includes at least two lidar systems of the same model;

If the target lidar system is mature, the uncertainty accuracy level of the target lidar system is calculated according to the filtered data set of the target.

Optionally, the refinement function and extension function of the program may refer to the above description.

Embodiments of the present application further provide a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, implements the above-mentioned classification method of a lidar system.

Optionally, the refinement function and extension function of the program may refer to the above description.

Finally, it should also be noted that in this document, relational terms such as and second are used only to distinguish one entity or operation from another, and do not necessarily require or imply these entities or operations. There is no such actual relationship or order between them. Moreover, the terms "comprising", "comprising" or any other variation thereof are intended to encompass a non-exclusive inclusion such that a process, method, article or device that includes a list of elements includes not only those elements, but also includes not explicitly listed or other elements inherent to such a process, method, article or apparatus. Without further limitation, an element qualified by the phrase "comprising a..." does not preclude the presence of additional identical elements in a process, method, article or apparatus that includes the element.

The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the various embodiments can be referred to each other.

The above description of the disclosed embodiments enables any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, this application is not intended to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method of ranking a lidar system, comprising:

acquiring a target data set, wherein the target data set at least comprises three data sets consisting of statistics of data collected by two laser radar systems of the same type and anemometry towers located in two sea areas under set conditions, the statistics at least comprise wind speed statistics, and the set conditions comprise at least one wave height;

eliminating invalid data in the target data set to obtain a target screened data set;

performing capture matrix statistics on the data set after the target screening to obtain a statistical result corresponding to the data set after the target screening, wherein the capture matrix is used for counting the number of statistical values of which wave heights are in all preset wave height intervals and wind speed statistical values are in all preset wind speed intervals, the total number of statistical values and the number of wave height intervals in all preset wind speed intervals, and the number of wave height intervals in a preset wind speed interval is the number of preset wave height intervals of which the number of statistical values is greater than or equal to a first number in the preset wind speed interval;

determining whether the number of statistical values contained in the target screened data set meets the requirement of a preset number or not according to the statistical result corresponding to the target screened data set;

if so, determining whether a target laser radar system is mature or not according to a statistical result corresponding to the data set after the target screening, wherein the target laser radar system at least comprises two laser radar systems with the same model;

and if the target laser radar system is mature, calculating the uncertainty precision level of the target laser radar system according to the data set after the target screening.

2. The method of grading a lidar system of claim 1, further comprising:

determining the effective rate of data according to the target screened data set and the target data set;

and determining whether the target laser radar system is mature or not according to the data effective rate, and executing capture matrix statistics on the data set after the target laser radar system is mature to obtain a statistical result corresponding to the data set after the target screening.

3. The grading method for lidar system of claim 2, wherein the target filtered data sets comprise at least filtered data sets corresponding to the three data sets respectively;

the acquiring the statistical result corresponding to the data set after the target screening by performing capture matrix statistics on the data set after the target screening includes:

for each screened data set contained in the target screened data set, performing capture matrix statistics on the screened data set to obtain a statistical result corresponding to the screened data set; obtaining a statistical result corresponding to each screened data set contained in the target screened data set;

the determining whether the number of the statistical values included in the target screened data set meets the requirement of a preset number according to the statistical result corresponding to the target screened data set includes:

for each screened data set contained in the target screened data set, determining whether the quantity of statistical values contained in the screened data set meets the preset quantity requirement or not according to the statistical result corresponding to the screened data set;

determining whether the target laser radar system is mature according to the statistical result corresponding to the data set after the target screening, including:

aiming at each screened data set contained in the target screened data set, determining whether a laser radar system corresponding to the screened data set is mature or not according to a statistical result corresponding to the screened data set; obtaining whether the laser radar system corresponding to each screened data set contained in the target screened data set is mature or not;

and if the laser radar systems corresponding to the screened data sets contained in the target screened data set are mature, determining that the target laser radar system is mature.

4. The grading method of the lidar system of claim 3, wherein the predetermined number requirement is that, in the statistical results corresponding to the filtered data set, the total number of statistical values in each predetermined wind speed interval is greater than or equal to the second number, the number of wave height intervals in each predetermined wind speed interval is greater than or equal to the third number, at least two predetermined wave height intervals satisfy the predetermined number quantum requirement, the predetermined number quantum requirement is that the total number of statistical values in the first wind speed interval and the second wind speed interval in a predetermined wave height interval is greater than or equal to the fourth number, and the total number of statistical values in the predetermined wave height interval is greater than or equal to the fifth number.

5. The method of claim 4, wherein the determining whether the lidar system corresponding to the filtered data set is mature according to the statistical result corresponding to the filtered data set comprises:

establishing a first linear regression equation for the wind speed statistic values in each preset wave height interval in the statistic results corresponding to the screened data set, and establishing a second linear regression equation for the wind speed statistic values in all preset wave height intervals to obtain the slope and the correlation coefficient corresponding to each first linear regression equation and the slope and the correlation coefficient corresponding to the second linear regression equation;

and determining whether the laser radar system corresponding to the screened data set is mature or not according to the slope and the correlation coefficient respectively corresponding to the first linear regression equation and the slope and the correlation coefficient corresponding to the second linear regression equation.

6. The grading method of lidar system of claim 1, wherein the wind speed statistic is a wind speed average, and the set condition further comprises at least one ground clearance;

calculating the uncertainty accuracy grade of the target laser radar system according to the data set after the target screening, including:

for each filtered data set contained in the target filtered data set:

classifying the screened data set according to the height above the ground to obtain at least one statistical value set corresponding to the height above the ground respectively;

determining final precision corresponding to the at least one ground clearance in the screened data set according to the statistic value set corresponding to the at least one ground clearance;

obtaining the final precision corresponding to the at least one ground clearance under each screened data set contained in the target screened data set;

and determining the uncertainty precision grade of the target laser radar system according to the final precision corresponding to the at least one ground clearance under each screened data set contained in the target screened data set.

7. The method according to claim 6, wherein the determining the final precision corresponding to the at least one ground clearance in the filtered data set according to the statistical value set corresponding to the at least one ground clearance respectively comprises:

calculating a value and a value range of the at least one ground clearance corresponding to preset environmental factors respectively according to the statistic value set corresponding to the at least one ground clearance respectively;

determining a target environment factor from preset environment factors according to a wind speed average value contained in a statistic value set corresponding to the at least one ground clearance respectively and a value of the at least one ground clearance corresponding to the preset environment factor respectively, wherein the target environment factor has a significant influence on an uncertainty precision level of the target laser radar system;

determining the maximum deviation of the at least one ground clearance corresponding to the target environmental factor respectively according to the equation slope and the value range of the at least one ground clearance corresponding to the target environmental factor respectively;

for each ground clearance in the at least one ground clearance, calculating initial precision corresponding to the ground clearance according to the maximum deviation of the ground clearance corresponding to the target environmental factor so as to obtain the initial precision corresponding to the at least one ground clearance respectively;

and dividing the initial precision corresponding to the at least one ground clearance by a preset value to obtain final precision corresponding to the at least one ground clearance as the final precision corresponding to the at least one ground clearance under the screened data set.

8. The grading method of lidar system according to claim 7, wherein the determining a target environmental factor from the preset environmental factors according to the wind speed average value included in the statistical value set corresponding to the at least one ground clearance and the value of the at least one ground clearance corresponding to the preset environmental factor respectively comprises:

calculating wind speed deviation percentages respectively corresponding to the at least one ground clearance according to wind speed average values contained in the statistical value sets respectively corresponding to the at least one ground clearance;

establishing a third linear regression equation according to the values of the preset environmental factors respectively corresponding to the at least one ground clearance and the wind speed deviation percentages respectively corresponding to the at least one ground clearance so as to obtain the third linear regression equation of which the at least one ground clearance respectively corresponds to the preset environmental factors;

determining an equation slope, a preset environmental factor standard deviation and a correlation coefficient according to a third linear regression equation of which the at least one ground clearance corresponds to the preset environmental factor respectively, wherein the equation slope, the preset environmental factor standard deviation and the correlation coefficient are used as the equation slope, the preset environmental factor standard deviation and the correlation coefficient of which the at least one ground clearance corresponds to the preset environmental factor respectively;

and determining a target environmental factor from the preset environmental factors according to the equation slope, the preset environmental factor standard deviation and the correlation coefficient of the at least one ground clearance corresponding to the preset environmental factor respectively.

9. The method for grading a lidar system according to claim 6, wherein the determining an uncertainty accuracy level of the target lidar system according to a final accuracy corresponding to the at least one ground clearance under each filtered data set included in the filtered data set comprises:

calculating the square sum of the final precision respectively corresponding to the at least one ground clearance under the target screened data set;

and squaring the sum of squares to obtain the uncertainty precision grade of the target laser radar system.

10. A classification apparatus for a lidar system, comprising: the system comprises a target data set acquisition module, an invalid data rejection module, a capture matrix statistical module, a quantity requirement satisfaction condition judgment module, a radar maturity judgment module and an uncertainty calculation module;

the target data set acquisition module is used for acquiring a target data set, wherein the target data set at least comprises three data sets consisting of statistics of data acquired by two laser radar systems of the same type and anemometry towers located in two sea areas under set conditions, the statistics at least comprises a wind speed statistic, and the set conditions comprise at least one wave height;

the invalid data removing module is used for removing invalid data in the target data set to obtain a target screened data set;

the capture matrix counting module is used for performing capture matrix counting on the data set after the target screening to obtain a statistical result corresponding to the data set after the target screening, wherein the capture matrix is used for counting the number of statistical values of which wave heights are in all preset wave height intervals and wind speed statistical values are in all preset wind speed intervals, the total number of the statistical values and the number of the wave height intervals in all preset wind speed intervals, and the number of the wave height intervals in a preset wind speed interval refers to the number of the preset wave height intervals of which the number of the statistical values in the preset wind speed interval is greater than or equal to a first number;

the quantity requirement meeting condition judging module is used for determining whether the quantity of statistical values contained in the target screened data set meets the preset quantity requirement or not according to the statistical result corresponding to the target screened data set;

the radar maturity judging module is configured to, if the quantity requirement satisfying condition judging module determines that the number of statistics values included in the target screened data set satisfies the preset quantity requirement, determine whether a target laser radar system is mature according to a statistical result corresponding to the target screened data set, where the target laser radar system at least includes the two laser radar systems of the same model;

and the uncertainty calculation module is used for calculating the uncertainty precision level of the target laser radar system according to the data set after target screening if the radar maturity judgment module determines that the target laser radar system is mature.

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