CN112241005B - Radar detection data compression method, device and storage medium - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/50—Systems of measurement based on relative movement of target
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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- H—ELECTRICITY
- H03—ELECTRONIC CIRCUITRY
- H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
- H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
- H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
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Abstract
本申请公开了一种雷达探测数据的压缩方法、装置及存储介质，属于数据处理领域。所述方法包括：根据雷达探测数据生成探测数据帧，所述探测数据帧包括雷达的M个天线在N个周期中每个周期内探测到的K个数据，所述M、N、K均为整数；对所述探测数据帧进行无损变换；根据无损变换后的探测数据帧的目标检测结果，获取关键探测数据和关键数据索引；根据所述关键探测数据和所述关键数据索引，确定压缩后的雷达探测数据。本申请可以提高压缩后的雷达探测数据的质量，而且还解决了因原始的雷达探测数据的数据量较大，不利于通过数据传输接口传输到计算机设备的问题。
The present application discloses a radar detection data compression method, device and storage medium, belonging to the field of data processing. The method comprises: generating a detection data frame according to radar detection data, the detection data frame comprising K data detected by M antennas of the radar in each of N cycles, wherein M, N and K are all integers; performing lossless transformation on the detection data frame; obtaining key detection data and key data index according to the target detection result of the detection data frame after lossless transformation; determining the compressed radar detection data according to the key detection data and the key data index. The present application can improve the quality of the compressed radar detection data, and also solves the problem that the original radar detection data has a large amount of data and is not conducive to being transmitted to a computer device through a data transmission interface.
Description
Technical Field
The present application relates to the field of data processing, and in particular, to a method and apparatus for compressing radar detection data, and a storage medium.
Background
Currently, radar can be used as a separate sensing device. That is, the radar may perform detection to obtain radar detection data, process the radar detection data to obtain target point information, and output the target point information to the computer device. The target point information may include, among other things, the speed of the target point, the distance between the target point and the radar, and the azimuth information of the target point. In other words, the computer device does not store the original radar detection data, but directly stores the target point information. Once the processed target point information is abnormal, the original radar detection data cannot be traced back, and the problem is difficult to be examined. However, the data amount of the radar detection data is often large, which is unfavorable for transmission to the computer device through the data transmission interface, and therefore, the radar detection data needs to be compressed and the compressed data needs to be output to the computer device.
Disclosure of Invention
The application provides a method, a device and a storage medium for compressing radar detection data, which can solve the problem that the original radar detection data has larger data quantity and is unfavorable for being transmitted to computer equipment through a data transmission interface in the related technology. The technical scheme is as follows:
in one aspect, there is provided a method of compressing radar detection data, the method comprising:
Generating a detection data frame according to radar detection data, wherein the detection data frame comprises K data detected by M antennas of a radar in each period of N periods, and M, N, K is an integer;
Performing lossless transformation on the detection data frame;
Acquiring key detection data and a key data index according to a target detection result of the detection data frame after lossless transformation;
and determining compressed radar detection data according to the key detection data and the key data index.
In one possible implementation manner, the obtaining the key detection data and the key data index according to the target detection result of the detection data frame after the lossless transformation includes:
generating a two-dimensional data matrix according to the detection data frame after the lossless transformation;
Determining a power matrix according to the two-dimensional data matrix, performing target detection on each data unit in the power matrix, and taking a position index of the data unit detected by the target as the key data index; or performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit detected by the target as the key data index;
And acquiring the key detection data from the detection data frame after lossless transformation according to the key data index.
In one possible implementation manner, the determining the compressed radar detection data according to the key detection data and the key data index includes:
and indexing the key detection data and the key data, and determining the key detection data and the key data as compressed radar detection data.
In one possible implementation manner, the determining the compressed radar detection data according to the key detection data and the key data index includes:
Determining the signal-to-noise ratio corresponding to each key data index according to the power matrix;
sequencing the key data indexes according to the order of the signal to noise ratio from large to small;
multiplying the total number of data units included in the power matrix by a reference compression rate to obtain L;
and determining data corresponding to the first L indexes in the index sorting result and the first L indexes as compressed radar detection data.
In one possible implementation manner, the determining the compressed radar detection data according to the key detection data and the key data index includes:
and determining the key detection data, the key data index and the power matrix as compressed radar detection data.
In one possible implementation manner, the determining the compressed radar detection data according to the key detection data and the key data index includes:
Determining the signal-to-noise ratio corresponding to each key data index according to the power matrix;
sequencing the key data indexes according to the order of the signal to noise ratio from large to small;
multiplying the total number of data units included in the power matrix by a reference compression rate to obtain L;
Compressing the power matrix according to the maximum power and the minimum power in the power matrix;
and determining key detection data corresponding to the first L indexes in the index sequencing result, the first L indexes and the compressed power matrix as compressed radar detection data.
In one possible implementation manner, the compressing the power matrix according to the maximum power and the minimum power in the power matrix includes:
And quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking a matrix formed by quantized data units as a compressed power matrix.
In another aspect, there is provided a radar detection data compression apparatus, the apparatus comprising:
The generation module is used for generating a detection data frame according to radar detection data, wherein the detection data frame comprises K data detected by M antennas of the radar in each period of N periods, and M, N, K is an integer;
the lossless conversion module is used for carrying out lossless conversion on the detection data frame;
The acquisition module is used for acquiring key detection data and a key data index according to the target detection result of the detection data frame after lossless transformation;
And the determining module is used for determining the compressed radar detection data according to the key detection data and the key data index.
In one possible implementation manner, the acquiring module includes:
the generating sub-module is used for generating a two-dimensional data matrix according to the detection data frame after lossless transformation;
the first determining submodule is used for determining a power matrix according to the two-dimensional data matrix;
The target detection sub-module is used for carrying out target detection on each data unit in the power matrix, and taking the position index of the data unit detected by the target as the key data index; or performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit detected by the target as the key data index;
And the acquisition sub-module is used for acquiring the key detection data from the detection data frame after the lossless transformation according to the key data index.
In one possible implementation, the determining module includes:
And the second determining submodule is used for indexing the key detection data and the key data and determining the key detection data and the key data as compressed radar detection data.
In one possible implementation, the determining module includes:
A third determining submodule, configured to determine, according to the power matrix, a signal-to-noise ratio corresponding to each key data index;
The first sorting sub-module is used for sorting the key data indexes according to the order of the signal to noise ratio from high to low;
A first operation submodule, configured to multiply a total number of data units included in the power matrix with a reference compression rate to obtain L;
And the fourth determining submodule is used for determining the data corresponding to the first L indexes in the index sorting result and the first L indexes as compressed radar detection data.
In one possible implementation, the determining module includes:
and a fifth determining sub-module, configured to determine the key detection data, the key data index, and the power matrix as compressed radar detection data.
In one possible implementation, the determining module includes:
A sixth determining submodule, configured to determine, according to the power matrix, a signal-to-noise ratio corresponding to each key data index;
the second sorting sub-module is used for sorting the key data indexes according to the order of the signal to noise ratio from high to low;
A second operation submodule, configured to multiply the total number of data units included in the power matrix with a reference compression rate to obtain L;
The compression submodule is used for compressing the power matrix according to the maximum power and the minimum power in the power matrix;
And a seventh determining submodule, configured to determine key sounding data corresponding to the first L indexes in the index sorting result, the first L indexes, and the compressed power matrix as compressed radar sounding data.
In one possible implementation, the compression submodule includes:
And the quantization unit is used for quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking the matrix formed by the quantized data units as a compressed power matrix.
In another aspect, a computer device is provided, where the computer device includes a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus, where the memory is used to store a computer program, and where the processor is used to execute the program stored on the memory, so as to implement the steps of the method for compressing radar detection data described above.
In another aspect, a computer readable storage medium is provided, in which a computer program is stored, which when executed by a processor, implements the steps of the method for compressing radar detection data described above.
In another aspect, there is provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the steps of the method of compression of radar detection data described above.
The technical scheme provided by the application has at least the following beneficial effects:
According to the method and the device, the compressed radar detection data can be determined according to the key detection data and the key data index, and the key detection data is the information of potential target points in the original radar detection data, so that the compressed radar detection data basically contains the information of most potential target points, namely, the compressed radar detection data is higher in quality and smaller in information loss. In addition, after data compression is carried out by the method provided by the embodiment of the application, the compressed radar detection data can be transmitted to the computer equipment, so that the problem that the original radar detection data is unfavorable to be transmitted to the computer equipment through a data transmission interface due to large data volume is solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic illustration of an implementation environment provided by an embodiment of the present application;
fig. 2 is a flowchart of a method for compressing radar detection data according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a data frame according to an embodiment of the present application;
Fig. 4 is a schematic structural diagram of a radar detection data compression device according to an embodiment of the present application;
Fig. 5 is a schematic structural diagram of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the embodiments of the present application will be described in further detail with reference to the accompanying drawings.
Before explaining the compression method of the radar detection data provided by the embodiment of the application in detail, the implementation environment provided by the embodiment of the application is described.
Referring to fig. 1, fig. 1 is a schematic diagram illustrating an implementation environment according to an exemplary embodiment. The implementation environment includes a radar 101 and a computer device 102. The radar 101 may be communicatively connected to the computer device 102. The communication connection may be a connection using a high-speed data transmission interface, which is not limited in this regard by the present application.
The radar 101 may perform detection to obtain radar detection data. The radar 101 may also process the radar detection data to obtain target point information, and compress the radar detection data. The target point information and the compressed radar detection data may then be transmitted to the computer device 102. As an example, the radar 101 may include M antennas, a radio frequency unit, and a data compression processing unit. The M antennas are used for receiving electromagnetic wave signals, and the radio frequency unit is used for generating radar detection data based on the electromagnetic wave signals received by the antennas. The data compression processing unit is configured to process the radar detection data to obtain target point information, compress the radar detection data, and transmit the target point information and the compressed radar detection data to the computer device 102.
The computer device 101 may receive target point information transmitted by the radar 101 and compressed radar detection data. The computer device 101 may also track the target point according to the target point information, and may also fuse the compressed radar detection data with the acquired image.
As an example, radar 101 may be a millimeter wave radar, a microwave radar, etc., and computer device 102 may be an electronic product that interacts with a user through one or more of a keyboard, a touchpad, a touch screen, a remote control, a voice interaction, or a handwriting device, such as a PC (Personal Computer ), a cell phone, a smart phone, a PDA (Personal DIGITAL ASSISTANT, a Personal digital assistant), a wearable device, a palm computer PPC (Pocket PC), a tablet, a smart car machine, a smart television, a smart speaker, etc.
Those skilled in the art will appreciate that the radar 101 and computer device 102 described above are by way of example only, and that other radar or computer devices, either now known or later developed, may be suitable for use with the present application and are intended to be within the scope of the present application and are incorporated herein by reference.
Next, a detailed explanation will be given of a method for compressing radar detection data provided by the embodiment of the present application.
Referring to fig. 2, fig. 2 is a flowchart illustrating a method for compressing radar detection data according to an exemplary embodiment, which may be applied to the radar 101 in the implementation environment shown in fig. 1. The method may include the following steps.
Step 201: and generating a detection data frame according to the radar detection data, wherein the detection data frame comprises K data detected by M antennas of the radar in each of N periods, and M, N, K are integers.
The radar may include M antennas, each of which may acquire radar detection data, and each of which may sample K times in one period. Further, since the radar performs data compression in units of data frames, the radar can generate a probe data frame from radar probe data according to a reference data format. Wherein, the parameter data format defines a period included in one data frame, namely N periods.
As an example, radar detection data may be data-arranged in three dimensions of sampling in a period, sampling during a period, and an antenna, so as to constitute a data frame as shown in fig. 3. The size of the data frame shown in fig. 3 is nxkxm, that is, the data frame shown in fig. 3 includes nxkxm data units. As such, for a data unit in the data frame shown in fig. 3, this data unit may be labeled s (k, n, m) representing the data of the kth sample point in the nth period of the mth antenna.
For example, suppose that the radar can sample 256 times per period, each data frame contains 128 periods, and the radar has 8 antennas in total. The size of each data frame is 256×128×8. If each sampling point is represented by 2 bytes (16 bits), the data amount of one data frame is 256×128×8×16=4 Mbps.
It should be noted that, the radar detection data is ADC (Analog-to-Digital Converter) data, which is generally non-intuitive data, and the radar may process the ADC data to extract information of a target point in the radar field of view at the current moment, where the information of the target point may generally include, but is not limited to, a speed of the target point, a distance between the target point and the radar, and azimuth information of the target point.
Step 202: and carrying out lossless transformation on the detection data frame.
As an example, each data in the sounding data frame may be fourier transformed. Wherein, since the Fourier transform is a reversible transform, no information is lost in the transform process, and therefore, no data loss is caused after the detection data frame is subjected to lossless transform according to the Fourier transform.
It should be noted that, in the embodiment of the present application, the lossless transformation of the probe data frame may be implemented through fourier transformation, and in other embodiments, the lossless transformation of the probe data frame may also be implemented through other transformation modes, which is not limited in the embodiment of the present application.
Step 203: and acquiring key detection data and a key data index according to the target detection result of the detection data frame after lossless transformation.
In some embodiments, a two-dimensional data matrix may be generated from the losslessly transformed probe data frames. A power matrix is determined from the two-dimensional data matrix. And performing target detection on each data unit in the power matrix, and determining the position index of the data unit passing the target detection in the power matrix as a key data index. And acquiring key detection data from the detection data frame after lossless transformation according to the key data index. Or generating a two-dimensional data matrix according to the detection data frame after lossless transformation. And performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit passing the target detection as a key data index. And acquiring key detection data from the detection data frame after lossless transformation according to the key data index.
For each data unit in the power matrix or the two-dimensional data matrix, if the data unit passes the target detection, it may be stated that the data unit may include information of the target point (for example, a speed of the target point, a distance between the target point and the radar, and azimuth information of the target point, etc.), the data unit is a data unit of the potential target point, and if the data unit does not pass the target detection, it may be stated that the data unit may not include data of the target point, and the data unit is not a data unit of the potential target point, in other words, the information amount of the data unit is low or an invalid data unit, and thus, compression of radar detection data is achieved by rejecting a part of the low information amount or invalid data unit. Therefore, the position index of the data unit detected by the target is determined as the key data index, so that omission of the key detection data can be avoided, and further data loss is reduced.
It should be noted that, when performing object detection on each data unit in the power matrix or the two-dimensional data matrix, potential object detection may be performed by a constant false alarm detection method, and in one example, if one data unit in the power matrix or the two-dimensional data matrix is subjected to constant false alarm detection, it is determined that a potential object exists, the data unit passes through object detection, and if one data unit is subjected to constant false alarm detection, it is determined that no potential object exists, then the data unit does not pass through object detection, and the data unit that does not pass through object detection may be rejected, so as to implement data compression. The potential target detection may also be performed by other detection methods, and the specific detection method is not limited in this embodiment of the present application.
As an example, from the losslessly transformed sounding data frame, the operation of generating a two-dimensional data matrix may be: and taking the modulus of each data in the detection data frame after lossless transformation, and accumulating the modulus-taken data according to the antenna dimension. That is, the data on the same antenna is accumulated. The accumulated data is data in both the period and the sampling point dimensions. Thus, a two-dimensional data matrix can be generated from the accumulated data. For example, for the above-mentioned n×k×m size probe data frame, each data in the probe data frame after lossless transformation is modulo, and the modulo data is accumulated according to the antenna dimension to obtain the n×k size two-dimensional data matrix.
As an example, the operation of determining the power matrix from the two-dimensional data matrix may be: each data element in the two-dimensional data matrix is converted into dB form, so that a power matrix can be obtained. In some embodiments, each data cell in the two-dimensional data matrix may be converted to dB form at 20log 10|sF |. Where s F is one data unit in the two-dimensional data matrix.
Because the two-dimensional data matrix comprises data in two dimensions of a period and a sampling point, and the power matrix is obtained by performing dB conversion on the data units in the two-dimensional data matrix, the position index of the data units detected by the target in the power matrix can be used as the position index in the two-dimensional data matrix.
As an example, according to the key data index, the operation of acquiring the key probe data from the probe data frame after the lossless transformation may be: and determining the data with the position indexes in the two dimensions of the period and the sampling point in the detection data frame after lossless conversion as the key detection data. That is, in the probe data frame after the lossless conversion, the data on the M antennas corresponding to the key data index is determined as the key probe data. For example, assuming that the index of the critical data includes the index of the 1 st row and the 2 nd position, the data acquired by the M antennas at this position may be determined as critical probe data.
It should be noted that, when performing object detection on each data unit in the power matrix or the two-dimensional data matrix, a detection threshold may be used, which may also be referred to as a first detection threshold, where the first detection threshold is used to determine the data amount of the radar detection data after compression. The first detection threshold may be sent to the radar by the computer device. The first detection threshold may be set by a user in a user-defined manner according to actual needs, or may be set by default by a computer device, which is not limited in the embodiment of the present application. In addition, the first detection threshold is generally set to be smaller, so that most of data units corresponding to potential target points can be guaranteed to be detected through targets.
Step 204: and determining the compressed radar detection data according to the key detection data and the key data index.
Since the critical probe data is part of the data in the lossless transformed data frame, in some embodiments, the critical probe data and the critical data index may be determined as compressed radar probe data. Therefore, compared with a data frame after lossless conversion, the data volume of the compressed radar detection data is relatively small, so that the problem that the original radar detection data is large in data volume and unfavorable for being transmitted to computer equipment through a data transmission interface can be solved, the information loss in the compressed radar detection data can be reduced, and the quality of data compression is improved.
In order to further reduce the data volume of the compressed radar detection data, the key detection data and the key data index may also be compressed. That is, the signal-to-noise ratio of each data corresponding to the key data index in the power matrix is determined. And sequencing the key data indexes according to the order of the signal to noise ratio from high to low. The total number of data units comprised by the power matrix is multiplied by the reference compression rate to obtain L. And determining the key detection data corresponding to the first L position indexes and the first L position indexes in the index sorting result as compressed radar detection data.
The reference compression rate is used to determine the data amount of the compressed radar detection data. And, the reference compression rate can be sent to the radar by the computer device, and the reference compression rate can be set by the user according to the actual requirement, or can be set by default by the computer device, which is not limited in the embodiment of the application.
For example, assume that the first detection threshold is 6dB and the reference compression rate is 2%. The size of the generated two-dimensional data matrix is 256×128 according to the detected data frame after lossless conversion. Thus, the total number of data units included in the power matrix is multiplied by the reference compression rate, and the resulting l=256×128×2% =655. Assuming that the number of data units detected by the target in the power matrix is 800, after the critical data indexes are ordered, critical probe data ordered after 655 may be discarded, and critical data indexes ordered after 655 may be discarded, and the remaining critical probe data and critical data indexes after being discarded may be used as compressed radar probe data.
As an example, the operation of determining the signal-to-noise ratio of each data corresponding to the key data index in the power matrix may be: for a first data unit in the power matrix, determining an average value of the data units in the neighborhood of the first data unit, determining a difference between the average value and the first data unit, and determining the difference as a signal to noise ratio of the first data unit. Wherein the first data unit is any data unit in the power matrix.
The size of the neighborhood can be sent to the radar by the computer device, the size of the neighborhood can be set by a user in a self-defined mode according to actual requirements, and the neighborhood can also be set by the computer device in a default mode, and the embodiment of the application is not limited in this way.
After the radar transmits the compressed radar detection data to the computer device, the computer device may need to fuse the radar detection data with the image. For this case, it is necessary to determine the power matrix as radar detection data in addition to the key detection data and the key data index as compressed radar detection data. That is, the critical sounding data, the critical data index, and the power matrix are determined as compressed radar sounding data.
In order to further reduce the data size of the compressed radar detection data, the key detection data, the index of the key detection data and the power matrix may be compressed. That is, the signal-to-noise ratio of each data corresponding to the key data index in the power matrix is determined. The key data is indexed into the row ordering in order of signal-to-noise ratio from large to small. The total number of data units comprised by the power matrix is multiplied by the reference compression rate to obtain L. And compressing the power matrix according to the maximum power and the minimum power in the power matrix. And determining the key detection data corresponding to the first L position indexes, the first L position indexes and the compressed power matrix in the sequencing result as compressed radar detection data.
As an example, the operation of compressing the power matrix according to the maximum power and the minimum power in the power matrix may be: and quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking the matrix formed by quantized data units as a compressed power matrix. In some embodiments, each data unit in the power matrix may be quantized according to the following equation based on the maximum power and the minimum power in the power matrix.
Wherein, in the above formula, P RD (n, k) represents the data unit of the nth row and the kth column in the power matrix, max (P RD) represents the maximum value in the power matrix, min (P RD) represents the minimum value in the power matrix, and B represents the number of quantized bits.
The above-mentioned B is used for determining the data amount of the compressed radar detection data. And B may be sent to the radar by the computer device. The B may be set by a user according to an actual requirement, or may be set by default by a computer device, which is not limited in the embodiment of the present application.
Since the critical probe data is complex data, the real part and the imaginary part are usually represented by 32-bit floating points, and assuming that B is 12, the data amount of the critical probe data corresponding to the first 655 position indexes is 655×8×32×2, the data amount of the first 655 position indexes is 655×16, and the data amount of the compressed power matrix is 256×128×12, so that when the compressed radar probe data includes the critical probe data corresponding to the first 655 position indexes and the first 655 position indexes, the data amount of the compressed radar probe data is 0.17Mbps. When the compressed radar detection data includes key detection data corresponding to the first 655 position indexes, and the compressed power matrix, the data amount of the compressed radar detection data is 0.545Mbps.
In summary, the above description is provided for data transmission between the radar and the computer device through the data transmission interface, where the data transmission interface has a certain transmission rate, and the first detection threshold, the reference compression rate, and B are used to determine the data amount of the compressed radar detection data, so before performing data compression, the computer device may determine whether the data amount of the compressed radar detection data is less than or equal to the transmission rate of the data transmission interface between the computer device and the radar after performing data compression according to the first detection threshold, the reference compression rate, and B stored by the computer device. If less than or equal to, then the first detection threshold, the reference compression rate, and B stored by itself may be sent to the radar. If the data size is larger than the first detection threshold, the reference compression rate and the reference compression rate, the computer device can also adjust the stored first detection threshold, the reference compression rate and the reference compression rate so that after the radar performs data compression according to the adjusted first detection threshold, the reference compression rate and the reference compression rate, the data size of the compressed radar detection data can be smaller than or equal to the transmission rate of a data transmission interface between the computer device and the radar. The computer device may then send the adjusted first detection threshold, the reference compression rate, and B to the radar.
In some embodiments, the amount of critical detected data and critical data indexed may be reduced by increasing the first detection threshold and the reference compression rate, and the amount of compressed power matrix may be reduced by decreasing B, so that the computer device may increase one or both of the stored first detection threshold and reference compression rate, or decrease B, as the stored first detection threshold, reference compression rate, and B are adjusted. Of course, the computer device may also be adjusted in other manners, as long as the radar performs data compression according to the adjusted first detection threshold, the reference compression rate and B, the data amount of the compressed radar detection data may be less than or equal to the transmission rate of the data transmission interface between the computer device and the radar, and the loss amount of the compressed radar detection data is small.
Thus far, the compression of the radar detection data has been completed. After the radar has determined the compressed radar detection data via steps 201-204 described above, the compressed radar detection data may be transmitted to a computer device. And the radar can also carry out subsequent processing on the compressed radar detection data. Since the radar detection data after compression may be different in different cases, a description will be given next of various cases.
In the first case, when the compressed radar detection data is the key detection data and the key data index, the data belonging to the same antenna in the key detection data can be processed according to the azimuth estimation algorithm to obtain azimuth information of a plurality of points. And clustering and tracking the points according to the distances between the points and the radar, the speeds of the points and the azimuth information of the points to obtain a tracking list of the target points, wherein the tracking list comprises the distances, the speeds and the azimuth information of the target points between different moments and the radar. The radar may transmit a tracking list of target points to the computer device.
It should be noted that the critical probe data may indicate the distances between the plurality of points and the radar, and the speeds of the plurality of points. In addition, after the key detection data is processed by the azimuth estimation algorithm, the obtained multiple points are scattered points, so that the multiple points can be clustered, and the target point is determined.
In the second case, when the compressed radar detection data includes the key detection data corresponding to the first L position indexes in the index sorting result and the first L position indexes, the key detection data corresponding to the first L position indexes in the index sorting result may be processed according to the processing manner of the first case, so as to obtain a tracking list of the target point, and the tracking list of the target point is transmitted to the computer device.
In the third case, when the compressed radar detection data includes the key detection data, the key data index, and the power matrix, the power matrix is subjected to target detection again, and the position index of the data passing through the target detection again is used as the azimuth data index. And acquiring data corresponding to the azimuth data index from the key detection data. The acquired data may be processed according to the processing manner of the first case, so as to obtain a tracking list of the target point, and the tracking list of the target point is transmitted to the computer device.
It should be noted that, when the power matrix is subjected to target detection again, a detection threshold is also used, and this detection threshold may be referred to as a second detection threshold. Since the first detection threshold is relatively small, substantially all potential target points can pass target detection, so that the power matrix can be subjected to target detection again to eliminate redundancy. Wherein the second detection threshold is greater than the first detection threshold.
The other point to be described is that when the power matrix is subjected to target detection again, the target detection can be performed by a constant false alarm detection method or by other detection methods. Moreover, the methods for performing the target detection twice on the power matrix may be the same or different, which is not limited in the embodiment of the present application.
It is noted that when the compressed radar detection data includes the key detection data, the key data index, and the power matrix, not only the processing can be performed according to the above method. The processing may also be performed directly in the first case, i.e. the power matrix may not be used.
In the fourth case, when the compressed radar detection data includes the key detection data corresponding to the first L position indexes in the index sorting result, the first L position indexes and the compressed power matrix, the processing may be performed according to the processing manner of the third case, so as to obtain a tracking list of the target point, and the tracking list of the target point is transmitted to the computer device.
According to the embodiment of the application, the compressed radar detection data can be determined according to the key detection data and the key data index, and the key detection data is the information of the potential target points in the original radar detection data, so that the compressed radar detection data basically contains the information of most potential target points, namely, the quality of the compressed radar detection data is higher, and the information loss is smaller. In addition, after data compression is carried out by the method provided by the embodiment of the application, the compressed radar detection data can be transmitted to the computer equipment, so that the problem that the original radar detection data is unfavorable to be transmitted to the computer equipment through a data transmission interface due to large data volume is solved.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a radar detection data compressing apparatus according to an exemplary embodiment, and the apparatus may be implemented as part or all of a radar, which may be the radar shown in fig. 1, by software, hardware, or a combination of both. The device comprises: a generation module 401, a lossless transformation module 402, an acquisition module 403, and a determination module 404.
The generating module 401 is configured to generate a detection data frame according to the radar detection data, where the detection data frame includes K data detected by M antennas of the radar in each of N periods, and M, N, K is an integer;
a lossless transform module 402, configured to perform lossless transform on the probe data frame;
An obtaining module 403, configured to obtain key detection data and a key data index according to a target detection result of the detection data frame after the lossless transformation;
A determining module 404, configured to determine the compressed radar detection data according to the key detection data and the key data index.
In one possible implementation, the obtaining module 403 includes:
the generating sub-module is used for generating a two-dimensional data matrix according to the detection data frame after lossless transformation;
the first determining submodule is used for determining a power matrix according to the two-dimensional data matrix;
The target detection sub-module is used for carrying out target detection on each data in the power matrix, and taking the position index of the data detected by the target as a key data index; or performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit passing the target detection as a key data index;
And the acquisition sub-module is used for acquiring the key detection data from the detection data frame after lossless transformation according to the key data index.
In one possible implementation, the determining module 404 includes:
and the second determining submodule is used for indexing the key detection data and the key data and determining the key detection data and the key data as compressed radar detection data.
In one possible implementation, the determining module 404 includes:
The third determining submodule is used for determining the signal-to-noise ratio corresponding to each key data index according to the power matrix;
the first ordering sub-module is used for ordering the key data indexes according to the order of the signal to noise ratio from high to low;
the first operation submodule is used for multiplying the total number of data included in the power matrix with a reference compression rate to obtain L;
And the fourth determining submodule is used for determining the data corresponding to the first L indexes and the first L indexes in the index sorting result as compressed radar detection data.
In one possible implementation, the determining module 404 includes:
And a fifth determining sub-module, configured to determine the key sounding data, the key data index and the power matrix as compressed radar sounding data.
In one possible implementation, the determining module 404 includes:
A sixth determining submodule, configured to determine, according to the power matrix, a signal-to-noise ratio corresponding to each key data index;
the second sequencing sub-module is used for sequencing the key data indexes according to the sequence from the high signal to noise ratio to the low signal to noise ratio;
The second operation submodule is used for multiplying the total number of data included in the power matrix with a reference compression rate to obtain L;
The compression sub-module is used for compressing the power matrix according to the maximum power and the minimum power in the power matrix;
and the seventh determining submodule is used for determining the key detection data corresponding to the first L indexes in the index sorting result, the first L indexes and the compressed power matrix as the compressed radar detection data.
In one possible implementation, the compression submodule includes:
And the quantization unit is used for quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking the matrix formed by the quantized data units as a compressed power matrix.
According to the embodiment of the application, the compressed radar detection data can be determined according to the key detection data and the key data index, and the key detection data is the information of the potential target points in the original radar detection data, so that the compressed radar detection data basically contains the information of most potential target points, namely, the quality of the compressed radar detection data is higher, and the information loss is smaller. In addition, after data compression is carried out by the method provided by the embodiment of the application, the compressed radar detection data can be transmitted to the computer equipment, so that the problem that the original radar detection data is unfavorable to be transmitted to the computer equipment through a data transmission interface due to large data volume is solved.
It should be noted that: the radar detection data compression device provided in the above embodiment is only exemplified by the division of the above functional modules when the radar detection data is compressed, and in practical application, the above functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to complete all or part of the functions described above. In addition, the compression device of the radar detection data provided in the above embodiment and the compression method embodiment of the radar detection data belong to the same concept, and the specific implementation process is detailed in the method embodiment, which is not described herein again.
Referring to fig. 5, fig. 5 is a block diagram illustrating a computer device 500 according to an exemplary embodiment. The computer device 500 may be a portable mobile terminal such as: a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, motion picture expert compression standard audio plane 3), an MP4 (Moving Picture Experts Group Audio Layer IV, motion picture expert compression standard audio plane 4) player, a notebook computer, or a desktop computer. Computer device 500 may also be referred to by other names of user devices, portable computer devices, laptop computer devices, desktop computer devices, and the like.
In general, the computer device 500 includes: a processor 501 and a memory 502.
Processor 501 may include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 501 may be implemented in at least one hardware form of DSP (DIGITAL SIGNAL Processing), FPGA (Field-Programmable gate array), PLA (Programmable Logic Array ). The processor 501 may also include a main processor and a coprocessor, where the main processor is a processor for processing data in an awake state, and is also called a CPU (Central Processing Unit ); a coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 501 may integrate a GPU (Graphics Processing Unit, image processor) for rendering and drawing of content required to be displayed by the display screen. In some embodiments, the processor 501 may also include an AI (ARTIFICIAL INTELLIGENCE ) processor for processing computing operations related to machine learning.
Memory 502 may include one or more computer-readable storage media, which may be non-transitory. Memory 502 may also include high-speed random access memory, as well as nonvolatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In some embodiments, a non-transitory computer readable storage medium in memory 502 is used to store at least one instruction for execution by processor 501 to implement the method of compression of radar detection data provided by the method embodiments of the present application.
In some embodiments, the computer device 500 may further optionally include: a peripheral interface 503 and at least one peripheral. The processor 501, memory 502, and peripheral interface 503 may be connected by buses or signal lines. Individual peripheral devices may be connected to peripheral device interface 503 by buses, signal lines, or circuit boards. Specifically, the peripheral device includes: at least one of radio frequency circuitry 504, touch display 505, camera 506, audio circuitry 507, positioning component 508, and power supply 509.
Peripheral interface 503 may be used to connect at least one Input/Output (I/O) related peripheral to processor 501 and memory 502. In some embodiments, processor 501, memory 502, and peripheral interface 503 are integrated on the same chip or circuit board; in some other embodiments, either or both of the processor 501, memory 502, and peripheral interface 503 may be implemented on separate chips or circuit boards, which is not limited in this embodiment.
The Radio Frequency circuit 504 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuitry 504 communicates with a communication network and other communication devices via electromagnetic signals. The radio frequency circuit 504 converts an electrical signal into an electromagnetic signal for transmission, or converts a received electromagnetic signal into an electrical signal. Optionally, the radio frequency circuit 504 includes: antenna systems, RF transceivers, one or more amplifiers, tuners, oscillators, digital signal processors, codec chipsets, subscriber identity module cards, and so forth. The radio frequency circuitry 504 may communicate with other computer devices via at least one wireless communication protocol. The wireless communication protocol includes, but is not limited to: the world wide web, metropolitan area networks, intranets, generations of mobile communication networks (2G, 3G, 4G, and 5G), wireless local area networks, and/or WiFi (WIRELESS FIDELITY ) networks. In some embodiments, the radio frequency circuit 504 may further include NFC (NEAR FIELD Communication) related circuits, which is not limited by the present application.
The display 505 is used to display a UI (User Interface). The UI may include graphics, text, icons, video, and any combination thereof. When the display 505 is a touch display, the display 505 also has the ability to collect touch signals at or above the surface of the display 505. The touch signal may be input as a control signal to the processor 501 for processing. At this time, the display 505 may also be used to provide virtual buttons and/or virtual keyboards, also referred to as soft buttons and/or soft keyboards. In some embodiments, the display 505 may be one, providing a front panel of the computer device 500; in other embodiments, the display 505 may be at least two, respectively disposed on different surfaces of the computer device 500 or in a folded design; in still other embodiments, the display 505 may be a flexible display disposed on a curved surface or a folded surface of the computer device 500. Even more, the display 505 may be arranged in a non-rectangular irregular pattern, i.e., a shaped screen. The display 505 may be made of LCD (Liquid CRYSTAL DISPLAY), OLED (Organic Light-Emitting Diode), or other materials.
The camera assembly 506 is used to capture images or video. Optionally, the camera assembly 506 includes a front camera and a rear camera. Typically, the front camera is disposed on a front panel of the computer device and the rear camera is disposed on a rear surface of the computer device. In some embodiments, the at least two rear cameras are any one of a main camera, a depth camera, a wide-angle camera and a tele camera, so as to realize fusion of the main camera and the depth camera to realize a background blurring function, fusion of the main camera and the wide-angle camera to realize a panoramic shooting and Virtual Reality (VR) shooting function or other fusion shooting functions. In some embodiments, camera assembly 506 may also include a flash. The flash lamp can be a single-color temperature flash lamp or a double-color temperature flash lamp. The dual-color temperature flash lamp refers to a combination of a warm light flash lamp and a cold light flash lamp, and can be used for light compensation under different color temperatures.
The audio circuitry 507 may include a microphone and a speaker. The microphone is used for collecting sound waves of users and environments, converting the sound waves into electric signals, and inputting the electric signals to the processor 501 for processing, or inputting the electric signals to the radio frequency circuit 504 for voice communication. The microphone may be provided in a plurality of different locations of the computer device 500 for stereo acquisition or noise reduction purposes. The microphone may also be an array microphone or an omni-directional pickup microphone. The speaker is used to convert electrical signals from the processor 501 or the radio frequency circuit 504 into sound waves. The speaker may be a conventional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, not only the electric signal can be converted into a sound wave audible to humans, but also the electric signal can be converted into a sound wave inaudible to humans for ranging and other purposes. In some embodiments, audio circuitry 507 may also include a headphone jack.
The location component 508 is used to locate the current geographic location of the computer device 500 to enable navigation or LBS (Location Based Service, location-based services). The positioning component 508 may be a positioning component based on the United states GPS (Global Positioning System ), the Beidou system of China, or the Galileo system of Russia.
The power supply 509 is used to power the various components in the computer device 500. The power supply 509 may be an alternating current, a direct current, a disposable battery, or a rechargeable battery. When the power supply 509 comprises a rechargeable battery, the rechargeable battery may be a wired rechargeable battery or a wireless rechargeable battery. The wired rechargeable battery is a battery charged through a wired line, and the wireless rechargeable battery is a battery charged through a wireless coil. The rechargeable battery may also be used to support fast charge technology.
In some embodiments, the computer device 500 further includes one or more sensors 510. The one or more sensors 510 include, but are not limited to: an acceleration sensor 511, a gyro sensor 512, a pressure sensor 513, a fingerprint sensor 514, an optical sensor 515, and a proximity sensor 516.
The acceleration sensor 511 can detect the magnitudes of accelerations on three coordinate axes of the coordinate system established with the computer device 500. For example, the acceleration sensor 511 may be used to detect components of gravitational acceleration on three coordinate axes. The processor 501 may control the touch display 505 to display a user interface in a landscape view or a portrait view according to a gravitational acceleration signal acquired by the acceleration sensor 511. The acceleration sensor 511 may also be used for acquisition of motion data of a game or a user.
The gyro sensor 512 may detect a body direction and a rotation angle of the computer apparatus 500, and the gyro sensor 512 may collect 3D actions of the user on the computer apparatus 500 in cooperation with the acceleration sensor 511. The processor 501 may implement the following functions based on the data collected by the gyro sensor 512: motion sensing (e.g., changing UI according to a tilting operation by a user), image stabilization at shooting, game control, and inertial navigation.
The pressure sensor 513 may be disposed on a side frame of the computer device 500 and/or on an underlying layer of the touch screen 505. When the pressure sensor 513 is disposed on the side frame of the computer device 500, a grip signal of the computer device 500 by a user may be detected, and the processor 501 performs left-right hand recognition or quick operation according to the grip signal collected by the pressure sensor 513. When the pressure sensor 513 is disposed at the lower layer of the touch display screen 505, the processor 501 controls the operability control on the UI interface according to the pressure operation of the user on the touch display screen 505. The operability controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.
The fingerprint sensor 514 is used for collecting the fingerprint of the user, and the processor 501 identifies the identity of the user according to the fingerprint collected by the fingerprint sensor 514, or the fingerprint sensor 514 identifies the identity of the user according to the collected fingerprint. Upon recognizing that the user's identity is a trusted identity, the user is authorized by the processor 501 to perform relevant sensitive operations including unlocking the screen, viewing encrypted information, downloading software, paying for and changing settings, etc. The fingerprint sensor 514 may be provided on the front, back or side of the computer device 500. When a physical key or vendor Logo is provided on the computer device 500, the fingerprint sensor 514 may be integrated with the physical key or vendor Logo.
The optical sensor 515 is used to collect the ambient light intensity. In one embodiment, the processor 501 may control the display brightness of the touch screen 505 based on the ambient light intensity collected by the optical sensor 515. Specifically, when the intensity of the ambient light is high, the display brightness of the touch display screen 505 is turned up; when the ambient light intensity is low, the display brightness of the touch display screen 505 is turned down. In another embodiment, the processor 501 may also dynamically adjust the shooting parameters of the camera assembly 506 based on the ambient light intensity collected by the optical sensor 515.
A proximity sensor 516, also referred to as a distance sensor, is typically provided on the front panel of the computer device 500. The proximity sensor 516 is used to collect the distance between the user and the front of the computer device 500. In one embodiment, the touch display 505 is controlled by the processor 501 to switch from the bright screen state to the off screen state as the proximity sensor 516 detects that the distance between the user and the front of the computer device 500 gradually decreases; when the proximity sensor 516 detects that the distance between the user and the front of the computer device 500 gradually increases, the touch display 505 is controlled by the processor 501 to switch from the off-screen state to the on-screen state.
Those skilled in the art will appreciate that the architecture shown in fig. 5 is not limiting as to the computer device 500, and may include more or fewer components than shown, or may combine certain components, or employ a different arrangement of components.
The present application shows a schematic diagram of a radar structure according to an exemplary embodiment, where the radar may have a relatively large difference due to different configurations or performances, and may include one or more processors (central processing units, CPU) and one or more memories, where at least one instruction is stored in the memories, and the at least one instruction is loaded and executed by the processor, so as to implement the method for compressing radar detection data in the foregoing embodiment. Of course, the radar may also have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing functions of the device, which are not described herein.
In some embodiments, there is also provided a computer readable storage medium having stored therein a computer program which, when executed by a processor, implements the steps of the radar detection data compression method of the above embodiments. For example, the computer readable storage medium may be ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.
It is noted that the computer readable storage medium mentioned in the present application may be a non-volatile storage medium, in other words, a non-transitory storage medium.
It should be understood that all or part of the steps to implement the above-described embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The computer instructions may be stored in the computer-readable storage medium described above.
That is, in some embodiments, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the steps of the radar detection data compression method described above.
The above embodiments are not intended to limit the present application, and any modifications, equivalent substitutions, improvements, etc. within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (14)
1. A method of compressing radar detection data, the method comprising:
Generating a detection data frame according to radar detection data, wherein the detection data frame comprises K data detected by M antennas of a radar in each period of N periods, and M, N, K is an integer;
Performing lossless transformation on the detection data frame;
Generating a two-dimensional data matrix according to the detection data frame after lossless transformation;
Determining a power matrix according to the two-dimensional data matrix, performing target detection on each data unit in the power matrix, and taking a position index of the data unit detected by the target as a key data index; or performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit detected by the target as the key data index;
Acquiring key detection data from the detection data frame after lossless transformation according to the key data index;
and determining compressed radar detection data according to the key detection data and the key data index.
2. The method of claim 1, wherein the determining compressed radar detection data from the key detection data and the key data index comprises:
and indexing the key detection data and the key data, and determining the key detection data and the key data as compressed radar detection data.
3. The method of claim 1, wherein the determining compressed radar detection data from the key detection data and the key data index comprises:
Determining the signal-to-noise ratio corresponding to each key data index according to the power matrix;
sequencing the key data indexes according to the order of the signal to noise ratio from large to small;
multiplying the total number of data units included in the power matrix by a reference compression rate to obtain L;
And determining data corresponding to the first L indexes in the index sorting result and the first L indexes as compressed radar detection data.
4. The method of claim 1, wherein the determining compressed radar detection data from the key detection data and the key data index comprises:
and determining the key detection data, the key data index and the power matrix as compressed radar detection data.
5. The method of claim 1, wherein the determining compressed radar detection data from the key detection data and the key data index comprises:
Determining the signal-to-noise ratio corresponding to each key data index according to the power matrix;
sequencing the key data indexes according to the order of the signal to noise ratio from large to small;
multiplying the total number of data units included in the power matrix by a reference compression rate to obtain L;
Compressing the power matrix according to the maximum power and the minimum power in the power matrix;
and determining key detection data corresponding to the first L indexes in the index sequencing result, the first L indexes and the compressed power matrix as compressed radar detection data.
6. The method of claim 5, wherein compressing the power matrix based on a maximum power and a minimum power in the power matrix comprises:
and quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking the matrix formed by quantized data units as a compressed power matrix.
7. A radar detection data compression apparatus, the apparatus comprising:
The generation module is used for generating a detection data frame according to radar detection data, wherein the detection data frame comprises K data detected by M antennas of the radar in each period of N periods, and M, N, K is an integer;
the lossless conversion module is used for carrying out lossless conversion on the detection data frame;
the acquisition module is used for acquiring key detection data and a key data index according to the target detection result of the detection data frame after lossless transformation;
The determining module is used for determining compressed radar detection data according to the key detection data and the key data index;
The acquisition module comprises:
the generating sub-module is used for generating a two-dimensional data matrix according to the detection data frame after lossless transformation;
the first determining submodule is used for determining a power matrix according to the two-dimensional data matrix;
The target detection sub-module is used for carrying out target detection on each data unit in the power matrix, and taking the position index of the data unit detected by the target as the key data index; or performing target detection on each data unit in the two-dimensional data matrix, and taking the position index of the data unit detected by the target as the key data index;
and the acquisition sub-module is used for acquiring the key detection data from the detection data frame after the lossless transformation according to the key data index.
8. The apparatus of claim 7, wherein the determining module comprises:
And the second determining submodule is used for indexing the key detection data and the key data and determining the key detection data and the key data as compressed radar detection data.
9. The apparatus of claim 7, wherein the determining module comprises:
A third determining submodule, configured to determine, according to the power matrix, a signal-to-noise ratio corresponding to each key data index;
the first sorting sub-module is used for sorting the key data indexes according to the order of the signal to noise ratio from high to low;
a first operation submodule, configured to multiply a total number of data units included in the power matrix with a reference compression rate to obtain L;
and the fourth determining submodule is used for determining the data corresponding to the first L indexes in the index sorting result and the first L indexes as compressed radar detection data.
10. The apparatus of claim 7, wherein the determining module comprises:
and a fifth determining sub-module, configured to determine the key detection data, the key data index, and the power matrix as compressed radar detection data.
11. The apparatus of claim 7, wherein the determining module comprises:
a sixth determining submodule, configured to determine, according to the power matrix, a signal-to-noise ratio corresponding to each key data index;
The second sorting sub-module is used for sorting the key data indexes according to the order of the signal to noise ratio from high to low;
A second operation submodule, configured to multiply the total number of data units included in the power matrix with a reference compression rate to obtain L;
the compression submodule is used for compressing the power matrix according to the maximum power and the minimum power in the power matrix;
And a seventh determining submodule, configured to determine key sounding data corresponding to the first L indexes in the index sorting result, the first L indexes, and the compressed power matrix as compressed radar sounding data.
12. The apparatus of claim 11, wherein the compression sub-module comprises:
And the quantization unit is used for quantizing each data unit in the power matrix according to the maximum power and the minimum power in the power matrix, and taking the matrix formed by the quantized data units as a compressed power matrix.
13. A computer device comprising a processor, a communication interface, a memory and a communication bus, said processor, said communication interface and said memory performing communication with each other via said communication bus, said memory being adapted to store a computer program, said processor being adapted to execute the program stored on said memory to carry out the steps of the method according to any one of claims 1-6.
14. A computer-readable storage medium, characterized in that the storage medium has stored therein a computer program which, when executed by a processor, implements the steps of the method of any of claims 1-6.
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