CN109975848B - Precision optimization method of mobile measurement system based on RTK technology - Google Patents

Abstract

The invention discloses a precision optimization method of a mobile measurement system based on an RTK technology, which comprises the following steps: s1, acquiring original data of a mobile measurement system, and measuring the relative position relation between an RTK receiver and the mobile measurement system to obtain an offset; s2, carrying out primary processing on the original data in the step S1 to obtain POS data; s3, calculating an RTK estimation value according to the POS data obtained in the step S2; s4, collecting data of the RTK receiver to obtain RTK data; s5, filtering a threshold value H according to the plane precision _Threshold And elevation precision filtering threshold value V _Threshold Filtering the RTK data collected in the step S4; s7, aligning the RTK estimated value and the RTK data, and calculating an RTK correction value; and S8, calculating new latitude values, longitude values and elevation values of the POS data at each moment based on the RTK correction values, and optimizing the POS data. The measurement data is optimized by the optimization method, and the measurement precision is improved.

Description

Accuracy optimization method of mobile measurement system based on RTK technology

Technical Field

The invention relates to the field of mobile measurement, and in particular to a method for optimizing the accuracy of a mobile measurement system based on RTK technology.

Background Art

The mobile measurement system is a hardware system that integrates satellite navigation system (GNSS), inertial measurement unit (IMU), laser radar (LiDAR) and other sensors. According to the different carriers, it can be divided into vehicle (ship) mounted, airborne, portable, etc. It can quickly collect surrounding 3D laser point cloud data during movement, and is a kind of surveying and mapping equipment.

When the existing mobile measurement system is used, first, a base station is set up at a known point near the measurement area to collect the original observation data of the GNSS satellite; then, the mobile measurement system is turned on, the IMU is initialized, and the GNSS and IMU data of the mobile station are synchronously saved and recorded; secondly, while the mobile carrier is moving forward, the data of GNNS, IMU, and LiDAR are synchronously recorded; finally, data processing is performed, and the original data of the GNSS base station and the GNSS mobile station are first differentially processed, and then the IMU data is fused to solve the POS data (position and attitude data), and then the time difference is used to obtain the position and attitude information of the platform at each point cloud collection moment, and then the point cloud coordinates are converted from the device coordinate system to the world coordinate system to obtain the point cloud result data.

However, because GNSS data is easily affected by the ionosphere during POS calculation and the distance between the GNSS base station and the mobile station is limited, the position accuracy of POS is generally not high, usually only reaching the decimeter level. In the worst case, the elevation error will exceed 1m. In addition, there is no feasible indicator to evaluate the accuracy of the collected data during the collection process.

To improve accuracy, general practices include:

1. Shorten the distance between the GNSS base station and the GNSS mobile station. According to experience, it is generally within 5 km.

2. Measure an external control point at a certain distance (for example, 50m), make local adjustments to the POS through the external control point, and then perform point cloud solution.

3. Avoid collecting data during active periods of the ionosphere.

In summary, in order to obtain high-precision point cloud data, the existing methods have the following shortcomings:

1. Setting up a GNSS base station near the survey area is time-consuming, labor-intensive, and labor-intensive. Generally, the survey area will exceed the 5km limit, requiring additional personnel and equipment, and requiring preliminary surveys of the survey area. In specific operations, the field costs will increase significantly.

2. Using external control points can effectively solve the problem of POS optimization, but the field workload is very large, and the control points are difficult to control and are easily blocked by traffic vehicles. Moreover, because the error of POS is uneven, a large number of control points are required. Therefore, there are great difficulties in implementation, and the implementation cost will be significantly increased. At the same time, the accuracy of the external control points is also difficult to control.

3. The ionosphere is active at different times in different regions, and the ionosphere activity level is difficult to determine in different seasons and weather conditions in the same region. Operators cannot determine whether the ionosphere is active and can only rely on experience.

Summary of the invention

The purpose of the present invention is to overcome the above-mentioned deficiencies in the prior art and provide a method for optimizing the accuracy of a mobile measurement system based on RTK technology, so as to optimize the measurement data of the mobile measurement system and improve the measurement accuracy.

In order to achieve the above-mentioned object of the invention, the present invention provides the following technical solutions:

A method for optimizing the accuracy of a mobile measurement system based on RTK technology comprises the following steps:

S1, collect the original data of the mobile measurement system, measure the relative position relationship between the RTK receiver antenna center and the mobile measurement system reference center, and obtain the offset;

S2, preliminarily processing the original data of step S1 to obtain POS data;

S3, calculating the RTK estimation value according to the POS data obtained in step S2; calculating the coordinate estimation value of the center of the RTK receiver antenna in the geodetic coordinate system based on the POS data, the offset value of the center of the RTK receiver antenna relative to the reference center of the mobile measurement system, and the attitude of the mobile measurement device;

S4, collecting data from the RTK receiver to obtain RTK data;

S5, filtering the RTK data collected in step S4 according to the plane accuracy filtering threshold H _Threshold and the elevation accuracy filtering threshold V _Threshold ;

S7, aligning the RTK estimated value and the RTK data, and calculating the RTK correction value;

S8, based on the RTK correction value, calculate the new latitude, longitude and altitude values of the POS data at each moment, and optimize the POS data.

旋转矩阵

计算方法如公式(1)和公式(2)所示：Preferably, the step S3 calculates the rotation matrix according to the posture of the mobile measurement device

Rotation Matrix

The calculation method is shown in formula (1) and formula (2):

Among them, _Ri is the attitude roll angle at time _ti , _Pi is the attitude pitch angle at time _ti , and _Yi is the attitude heading angle at time _ti .

Preferably, the calculation formula of the RTK estimation value in step S3 is as shown in formula (3):

为POS数据记录的t_i时刻的纬度，

为POS数据记录的t_i时刻的经度，

为POS数据记录的t_i时刻的高程，

为t_i时刻RTK接收器天线中心与移动测量系统参考中心的X轴偏移、

为ti时刻RTK接收器天线中心与移动测量系统参考中心的Y轴偏移，

为t_i时刻RTK接收器天线中心与移动测量系统参考中心的Z轴偏移参数。in,

is the latitude of the POS data record at time t _i ,

is the longitude at time t _i recorded in the POS data,

is the elevation at time t _i recorded by POS data,

is the X-axis offset between the RTK receiver antenna center and the mobile measurement system reference center at time t _i ,

is the Y-axis offset between the RTK receiver antenna center and the mobile measurement system reference center at time ti,

is the Z-axis offset parameter between the RTK receiver antenna center and the reference center of the mobile measurement system at time t _i .

Preferably, the plane filtering condition in step S5 is that H _Dop satisfies |H _Dop |<H _Threshold ; the elevation filtering condition is |V _Dop |<V _Threshold ; wherein H _Dop represents the plane accuracy at the tth moment, V _Dop represents the elevation accuracy at the tth moment, H _Threshold is the plane accuracy filtering threshold, and V _Threshold is the elevation accuracy filtering threshold.

与RTK估计值

的差值，得到第i时刻的纠正值，计算公式如公式(4)所示：Preferably, the step S7 calculates the RTK data at the i-th moment

With RTK estimate

The difference between the values of and is used to obtain the correction value at the i-th moment. The calculation formula is shown in formula (4):

为第i时刻的纬度修正值，

为第i时刻的经度修正值，

为第i时刻的高程修正值，即第i时刻的RTK纠正值记为

in,

is the latitude correction value at the i-th moment,

is the longitude correction value at the i-th moment,

is the elevation correction value at the i-th moment, that is, the RTK correction value at the i-th moment is recorded as

Preferably, the method of optimizing POS data in step 8 is as follows;

数据中查找时间不大于t₁的最大时间t′₁和时间大于t₁的最小时间t″₁，则t₁、t′₁和t″₁满足关系：t′₁≤t₁<t″₁；The POS data at time _t1 is _Pt1 = ( _t1 , _BP1 , _LP1 , _HP1 , R, P, Y). First, the POS data that meets the plane filtering conditions is

Find the maximum time t′ ₁ that is not greater than t ₁ and the minimum time t″ ₁ that is greater than t ₁ in the data, then t ₁ , t′ ₁ and t″ ₁ satisfy the relationship: t′ ₁ ≤t ₁ <t″ ₁ ;

t″₁时刻的RTK数据对应的纠正值

利用插值算法，计算t₁时刻新的POS经度B′₁、纬度值L′₁和高程值H′₁。Correction value corresponding to the RTK data at time t1′

Correction value corresponding to the RTK data at time t″ ₁

Using the interpolation algorithm, calculate the new POS longitude B′ ₁ , latitude L′ ₁ and elevation H′ ₁ at time t ₁ .

Preferably, the interpolation algorithm adopts a time-based linear interpolation method, and the interpolation calculation method is shown in formula (5) and formula (6):

Wherein B′ ₁ , L′ ₁ and H′ ₁ are respectively the new latitude, longitude and elevation values of the POS data at time t ₁ obtained by interpolation. The new latitude, longitude and elevation values of the POS data at each time are calculated according to the optimization method to optimize the POS data.

Preferably, the method for optimizing the accuracy of a mobile measurement system based on RTK technology further comprises step S6, wherein step S6 is located between step S5 and step S7, and the filtered data obtained in step S5 are sorted according to time.

Compared with the prior art, the present invention has the following beneficial effects:

1. Obtain positioning data based on RTK technology. Since most areas are currently covered by the CORS system, any RTK device can be connected to the CORS system to obtain high-precision surveying and mapping-level positioning data, which is convenient to implement and has high availability.

2. Use the data of existing CORS base stations for POS calculation, without the need to set up a separate GNSS base station. If a base station is to be set up, there is no 5km distance limit, and it is feasible within tens of kilometers, which greatly increases the operating range and saves manpower and equipment;

3. The plane accuracy and elevation accuracy obtained by the RTK receiver can be used to obtain the positioning accuracy of the current equipment. This accuracy is basically consistent with the accuracy of the result data. Therefore, during the acquisition process, the operator can know the approximate accuracy of the result data through the plane accuracy and elevation accuracy. The operation process can be accurately indicated and controlled based on the plane accuracy and elevation accuracy. For example, in the case of poor accuracy, a deceleration and parking instruction can be issued;

4. Optimize data processing to improve measurement accuracy, and eliminate the need for a large number of external control point measurements, saving a lot of manpower and shortening the field operation cycle.

Description of the drawings:

FIG1 is a flow chart of a method for optimizing the accuracy of a mobile measurement system based on RTK technology according to an exemplary embodiment 1 of the present invention;

FIG. 2 is a flowchart of a method for optimizing the accuracy of a mobile measurement system based on RTK technology according to an exemplary embodiment 2 of the present invention.

DETAILED DESCRIPTION

The present invention is further described in detail below in conjunction with test examples and specific implementation methods. However, this should not be understood as the scope of the above subject matter of the present invention being limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

Example 1

The CORS (Continuously Operating Reference Stations) system is a high-precision measurement method commonly used in the field of surveying and mapping. It generally uses RTK (Real-time kinematic) carrier phase differential technology to measure point by point, which has high accuracy but low efficiency. This embodiment combines the CORS system, RTK technology and mobile measurement technology to solve the absolute accuracy problem of point cloud data of mobile measurement system.

The basic idea is to connect an RTK receiver to the mobile measurement system, synchronously record the RTK positioning data during the acquisition process, and record it once at a fixed time. The recorded data includes the following information: time (year, month, day, hour, minute, second), longitude, latitude, elevation, plane accuracy and elevation accuracy. The relative position relationship between the RTK receiver antenna center and the mobile measurement system reference center is obtained by measurement, and the offset relationship includes: X-axis offset, Y-axis offset and Z-axis offset (using the right-handed coordinate system, that is, when the X-axis is right, the Y-axis is forward and the Z-axis is upward).

As shown in FIG1 , this embodiment provides a method for optimizing the accuracy of a mobile measurement system based on RTK technology, which specifically includes the following steps:

S1, collects sensor data such as satellite navigation system (GNSS), inertial measurement unit (IMU) and laser radar (LiDAR) in the mobile measurement system, as well as data from the CORS system; and measures the relative position relationship between the center of the RTK receiver antenna and the reference center of the mobile measurement system to obtain the offset;

S2, preliminarily processing the original data of step S1 to obtain POS data;

The raw data of the satellite navigation system (GNSS) in the CORS system and the mobile measurement system are processed, and then the IMU data and LiDAR data are integrated to solve the POS data. The POS data at the tth time represents the coordinates of the geodetic coordinate system of the reference center of the mobile measurement system, which is recorded as _Pt = (t, _BP , _LP , _HP , R, P, Y), where t represents the tth time, _BP represents the latitude at the tth time, _LP represents the longitude at the tth time, _HP represents the altitude at the tth time, R represents the roll angle of the device at the tth time, P represents the pitch angle of the device at the tth time, and Y represents the heading angle of the device at the tth time.

S3, calculating the RTK estimation value according to the POS data obtained in step S2;

The RTK estimated value at time t indicates, at time t, the estimated coordinate value of the RTK receiver antenna center in the geodetic coordinate system calculated based on the POS data, the offset value of the RTK receiver antenna center relative to the reference center of the mobile measurement system, and the attitude of the mobile measurement device.

根据POS数据记录的纬度

经度

高程

及t_i时刻RTK接收器天线中心与移动测量系统参考中心的X轴偏移

Y轴偏移

Z轴偏移参数

以及由t_i时刻的姿态侧滚角R_i、俯仰角P_i、航向角Y_i构建的旋转矩阵

计算在t_i时刻对应的RTK估计值

其中

表示t_i时刻估计值的纬度，

表示t_i时刻估计值的经度，

表示t_i时刻估计值的高程。旋转矩阵

计算方法如公式(1)和公式(2)所示：For example, to find the POS data at time t _i , record it as

Latitude recorded according to POS data

longitude

Elevation

and the X-axis offset between the RTK receiver antenna center and the mobile measurement system reference center at time t _i

Y-axis offset

Z-axis offset parameters

And the rotation matrix constructed by the attitude roll angle R _i , pitch angle P _i , and heading angle Y _i at time t _i

Calculate the RTK estimate corresponding to time t _i

in

represents the latitude of the estimated value at time t _i ,

represents the longitude of the estimated value at time t _i ,

Represents the elevation of the estimated value at time t _i . Rotation matrix

The calculation method is shown in formula (1) and formula (2):

The calculation formula of RTK estimation value is shown in formula (3):

S4, collecting data from the RTK receiver to obtain RTK data;

The RTK data at time t represents the geodetic coordinate system coordinate of the center of the RTK receiver antenna, recorded as R _t =(t, _BR , _LR , _HR , H _Dop , V _Dop ), where t represents time, _BR represents latitude at time t, _LR represents longitude at time t, _HR represents elevation at time t, H _Dop represents plane accuracy at time t, and V _Dop represents elevation accuracy at time t.

S5, filtering the RTK data collected in step S4 according to the plane accuracy filtering threshold H _Threshold and the elevation accuracy filtering threshold V _Threshold ;

高程过滤条件为，|V_Dop|<V_Threshold(|V_Dop|表示对V_Dop取绝对值)，符合高程过滤条件的RTK数据记为

RTK数据通过过滤得到一系列的

和

数据，分别记为

和

Set the plane accuracy filtering threshold H _Threshold and the elevation accuracy filtering threshold V _Threshold . The plane filtering condition is that H _Dop satisfies |H _Dop |<H _Threshold (|H _Dop | means taking the absolute value of H _Dop ). The RTK data that meets the plane filtering condition is recorded as

The elevation filtering condition is, |V _Dop |<V _Threshold (|V _Dop | means taking the absolute value of V _Dop ). The RTK data that meets the elevation filtering condition is recorded as

RTK data is filtered to obtain a series of

and

Data are recorded as

and

S7, aligning the RTK estimated value and the RTK data, and calculating the RTK correction value;

与RTK估计值

的差值，即得到第i时刻的纠正值，计算公式如公式(4)所示：For example, calculate the RTK data at time i

With RTK estimate

The difference between the values of , that is, the correction value at the i-th moment is obtained. The calculation formula is shown in formula (4):

为第i时刻的纬度修正值，

为第i时刻的经度修正值，

为第i时刻的高程修正值，即第i时刻的RTK纠正值记为

以此方法计算所有RTK数据对应的RTK纠正值。in,

is the latitude correction value at the i-th moment,

is the longitude correction value at the i-th moment,

is the elevation correction value at the i-th moment, that is, the RTK correction value at the i-th moment is recorded as

This method is used to calculate the RTK correction values corresponding to all RTK data.

S8, based on the RTK correction value, calculate the new latitude, longitude and altitude values of the POS data at each moment, and optimize the POS data.

数据中查找时间不大于t₁的最大时间t′₁和时间大于t₁的最小时间t″₁，则t₁、t′₁和t″₁满足关系：t′₁≤t₁<t″₁。For example, assuming that the POS data at time _t1 is _Pt1 = ( _t1 , _BP1 , _LP1 , _HP1 , R, P, Y), first select the POS data that meets the plane filtering conditions.

Find the maximum time t′ ₁ that is not greater than t ₁ and the minimum time t″ ₁ that is greater than t ₁ in the data, then t ₁ , t′ ₁ and t″ ₁ satisfy the relationship: t′ ₁ ≤t ₁ <t″ ₁ .

t″₁时刻的RTK数据对应的纠正值

利用插值算法，计算t₁时刻新的POS经度B′₁、纬度值L′₁和高程值H′₁，其它值保持不变。以基于时间的线性插值方法为例，插值计算方法如公式(5)和公式(6)所示：Correction value corresponding to the RTK data at time t′ ₁

Correction value corresponding to the RTK data at time t″ ₁

Using the interpolation algorithm, calculate the new POS longitude B′ ₁ , latitude L′ ₁ and elevation H′ ₁ at time t ₁ , and keep other values unchanged. Taking the time-based linear interpolation method as an example, the interpolation calculation method is shown in formula (5) and formula (6):

Wherein B′ ₁ , L′ ₁ and H′ ₁ are respectively the new latitude, longitude and elevation values of the POS data at time t ₁ obtained by interpolation. According to this method, the new latitude, longitude and elevation values of the POS data at each time are calculated to optimize the POS data.

The positioning data of this embodiment is obtained based on RTK technology. Since most areas are currently covered by the CORS system, any RTK device can be used to access the CORS system to obtain high-precision surveying and mapping-level positioning data, which is easy to implement and has high availability. In addition, the data of existing CORS base stations are used for POS solution, and there is no need to set up a GNSS base station separately. If a base station is to be set up, there is no distance limit of 5Km, and it is feasible within tens of kilometers, which greatly increases the operating range and saves manpower and equipment. The plane accuracy and elevation accuracy obtained by the RTK receiver can obtain the positioning accuracy of the current equipment. This accuracy is basically consistent with the accuracy of the result data. Therefore, the operator can know the approximate accuracy of the result data through the plane accuracy and elevation accuracy during the collection process, and can accurately indicate and control the operation process according to the plane accuracy and elevation accuracy. For example, in the case of poor accuracy, a deceleration and stop instruction can be issued. The technical solution described in this embodiment is used to optimize the data, improve the measurement accuracy, and does not require a large amount of external control point measurement work, saving a lot of manpower and shortening the field operation cycle.

Example 2

和

数据，分别按照时间t进行排序；对数据进行排序，便于后续数据的处理，提高处理速度。As shown in FIG2 , this embodiment provides a method for optimizing the accuracy of a mobile measurement system based on RTK technology. Compared with the method for optimizing the accuracy described in Example 1, the method further includes step S6; step S6 is located between step S5 and step S7, and the method obtains the value of the value obtained in step S5.

and

The data are sorted according to time t respectively; sorting the data facilitates the subsequent data processing and improves the processing speed.

The above is only a detailed description of the specific implementation of the present invention, rather than a limitation of the present invention. Various substitutions, modifications and improvements made by those skilled in the relevant art without departing from the principle and scope of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. A precision optimization method of a mobile measurement system based on an RTK technology is characterized by comprising the following steps:

s1, acquiring original data of a mobile measurement system, and measuring a relative position relation between an antenna center of an RTK receiver and a reference center of the mobile measurement system to obtain an offset;

s2, carrying out primary processing on the original data in the step S1 to obtain POS data;

s3, calculating an RTK estimation value according to the POS data obtained in the step S2; calculating a geodetic coordinate system coordinate estimation value of the RTK receiver antenna center based on the POS data, the offset value of the RTK receiver antenna center relative to the reference center of the mobile measurement system and the mobile measurement equipment attitude;

the calculation formula of the RTK estimated value is shown as formula (3):

wherein,

t recorded for POS data _i Latitude at that moment>

T recorded for POS data _i The longitude of the moment in time>

T recorded for POS data _i The elevation of the moment>

Is t _i X-axis offset of the time RTK receiver antenna center from the reference center of the mobile measurement system, <' > or>

Is t _i The Y-axis offset of the time RTK receiver antenna center from the mobile measurement system reference center,

is t _i Z-axis offset parameter of antenna center and reference center of mobile measurement system of time RTK receiver；

Is a rotation matrix;

s4, collecting data of the RTK receiver to obtain RTK data;

s5, filtering a threshold value H according to the plane precision _Threshold And height precision filtering threshold V _Threshold Filtering the RTK data collected in the step S4;

s7, aligning the RTK estimated value and the RTK data, and calculating an RTK correction value;

by calculating the RTK data at the ith time

And the RTK estimate->

The corrected value at the ith moment is obtained, and the calculation formula is shown as formula (4):

wherein,

is a latitude correction value at the i-th moment>

Is a longitude correction value at instant i>

Is an elevation correction value at the i-th time, i.e. the RTK correction value at the i-th time is recorded as->

S8, calculating new latitude values, longitude values and elevation values of the POS data at each moment based on the RTK correction values, and optimizing the POS data;

the method of optimizing POS data is as follows;

t ₁ POS data of time is P _t1 ＝(t ₁ ，B _P1 ，L _P1 ，H _P1 R, P, Y), first in accordance with the planar filtration conditions

The search time in the data is not more than t ₁ Of maximum time t' ₁ And time greater than t ₁ Minimum time t " ₁ Then t is ₁ 、t' ₁ And t' ₁ Satisfies the relationship: t' ₁ ≤t ₁ <t” ₁ ；/>

According to t' ₁ Correction value corresponding to RTK data of time

t” ₁ Correction value based on RTK data at time->

Calculating t using an interpolation algorithm ₁ Time of day new POS longitude B' ₁ L 'weft value' ₁ And an elevation value H' ₁ 。

2. The method for optimizing accuracy of a RTK-based mobile measurement system of claim 1, wherein said step S3 is to calculate a rotation matrix according to the attitude of the mobile measurement device

Rotating matrix->

The calculation method is shown in formula (1) and formula (2):

wherein R is _i Is t _i Attitude roll angle at time, P _i Is t _i Attitude pitch angle at time, Y _i Is t _i The attitude heading angle at the moment.

3. The RTK-based kinematic measurement system accuracy optimization method of claim 1, wherein the step S5 plane filtering condition is H _Dop Satisfy | H _Dop |<H _Threshold (ii) a The elevation filtering condition is, | V _Dop |<V _Threshold (ii) a Wherein H _Dop Indicating the plane accuracy, V, at time t _Dop Indicating the elevation accuracy at time t, H _Threshold Filtering the threshold for planar precision, V _Threshold A threshold is filtered for elevation precision.

4. An RTK technology based movement measurement system accuracy optimization method according to claim 1, characterized in that the interpolation algorithm uses a time based linear interpolation method, the interpolation calculation method is shown in formula (5) and formula (6):

wherein B' ₁ 、L' ₁ And H' ₁ T obtained for interpolation respectively ₁ And calculating the new latitude value, longitude value and elevation value of the POS data at each moment according to the optimization method, and optimizing the POS data.

5. A method for optimizing accuracy of a mobile measurement system based on an RTK technique according to any of claims 1 to 4, characterized in that it further comprises a step S6, wherein said step S6 is located between step S5 and step S7, and the filtered data obtained in step S5 are sorted according to time.

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