Millimeter wave radar distance azimuth map extraction method and device

Abstract

The invention discloses a millimeter wave radar distance azimuth map extraction method and device, and the method comprises the steps: extracting a data matrix, carrying out the coherent accumulation of the data matrix along the dimension of a virtual receiving channel, carrying out the Fourier transform, obtaining an absolute value, carrying out the Doppler peak detection, converting the Doppler peak position into Doppler phase shift, and carrying out the Doppler phase shift. Distributing weights according to the sizes of pks of different peak values, calculating a sum value, normalizing the sum value, and constructing a corresponding compensation matrix according to the size of the data matrix; and compensating the data matrix according to the compensation matrix, and executing subsequent steps of the MVDR algorithm to obtain an RA map. According to the method, the mvdr process is optimized, Doppler compensation in a multi-target environment is carried out, the influence of target Doppler on the RA image is eliminated, and the obtained RA image is higher in angle precision; the target peak wave beam is narrower, and the extension in the distance dimension and the angle dimension is smaller; the target peak energy value is larger, and the signal-to-noise ratio is higher.

Description

Technical Field

[0001] The present invention relates to the field of millimeter wave radar-video fusion, and in particular to a method and device for extracting a millimeter wave radar range and azimuth map. Background Art

[0002] In millimeter-wave radar-video fusion technology, the fusion data of each sensor can come from different positions in the data processing link. According to the location of the data source and the information contained, the fusion behavior can be divided into pre-fusion and post-fusion. Pre-fusion pre-processes and extracts features from the raw data from different sensors to provide better input for the subsequent fusion process. In the millimeter-wave radar signal and data processing link, different levels of data can be output at different time nodes. Common data processing links are as follows:

[0003] Adc signal→Radar cube→Range-Doppler-Azimuth tensor→Point cloud→tracking objects

[0004] In the common post-fusion processing, the data source of the radar side is often point cloud or tracking objects. At this time, the input data has less information and high accuracy, which has a low upper limit for the fusion algorithm. In order to obtain more information-rich data in the fusion stage, the pre-fusion often uses the Range-Doppler-Azimuth tensor, the so-called RA / RD map (range azimuth heat map / range doppler heat map). This proposal focuses on the extraction method of the RA map and the quality of the RA map, so this aspect will be explained next.

[0005] Method to obtain RA graph: Perform 1d FFT on each receiving channel and each chirp of radar cube to obtain the distance dimension result, and arrange the results in order to obtain 1dfft radar cube. Then extract the vector data of single chirp multi-channel or matrix data of multi-chirp multi-channel in the order of range bin from 1dfft radar cube for direction of arrival estimation. Common methods include digital beamforming (DBF), minimum variance distortionless response (MVDR), multiple signal classification algorithm (MUSIC), etc. After the direction of arrival is estimated for each rangebin, we can get the Range-Azimuth graph, i.e. RA graph. After obtaining the RA graph, we can know the distribution of targets in the radar detection range in two dimensions of distance and horizontal angle, which is a good input for the fusion algorithm with video images.

[0006] Among the commonly used methods, DBF requires multi-channel data of at least one chirp to obtain the RA diagram, but its angular resolution is low, which is basically equivalent to directly performing angular FFT. In addition, since only one chirp's data is used, the process is greatly affected by noise; MVDR and music require data from multiple chirps to construct the data noise covariance matrix. Their angular resolution is higher than that of DBF, and the target beam width is narrower, which can better distinguish adjacent targets in the angular dimension. The actual fusion algorithm often uses the mvdr or music algorithm. Among them, since the music algorithm involves the eigenvalue decomposition of the matrix, it introduces a large amount of calculation, and requires prior information on the number of signal sources, the mvdr method is widely used in engineering practice.

[0007] Whether it is MVDR or MUSIC, multiple chirp data are needed to construct the data noise covariance matrix. In order to obtain the data noise covariance matrix better and more accurately, a larger number of chirps are often required, which will introduce the influence of the target Doppler. Especially in TDM (time division multiplex) or BPM (bi-phase multiplex) modulation modes, since different virtual receiving channels are generated in different chirps, the corresponding Doppler frequency shift will inevitably be generated due to the target Doppler, resulting in the introduction of corresponding errors during DoA. Summary of the invention

[0008] The present invention aims to solve the problems in the prior art and to provide a method for extracting a millimeter wave radar range and azimuth map.

[0009] The object of the present invention is achieved through the following technical scheme: a method for extracting a millimeter wave radar range azimuth map, the method comprising:

[0010] S1. Traverse each distance unit in the millimeter wave radar to obtain a data matrix, the size of which is obtained by the number of virtual receiving channels and the chirp sent by the radar in one frame;

[0011] S2, coherently accumulate the data matrix along the dimension of the virtual receiving channel, then perform Fourier transform of the chirp dimension and take the absolute value;

[0012] S3, performing Doppler peak detection on the sequence processed by S2 to obtain the Doppler peak position;

[0013] S4, converting the Doppler peak position into the Doppler phase shift, assigning weights according to the pks of different peaks and calculating the sum, normalizing the sum and constructing the corresponding compensation matrix according to the size of the data matrix;

[0014] S5. Compensate the data matrix according to the compensation matrix, calculate the data noise defense difference according to the compensated data matrix, traverse each angle to calculate the steering vector, calculate the response of the MVDR filter at each angle, and integrate the results into the millimeter wave radar range and azimuth map.

[0015] Furthermore, the extraction of the data matrix specifically includes: traversing each distance unit, extracting a data matrix X1 of size Nchannel*Nchirp from the radar data matrix that has undergone a fast Fourier transform in the distance dimension, wherein Nchannel represents the number of virtual receiving channels, and Nchirp represents the number of chirps sent by the radar in one frame.

[0016] Furthermore, the specific steps in S2 are:

[0017]

[0018] X1_fft_abs=abs(fft(X1 array ,Nfft))

[0019] Where X1 is the extracted data matrix, Nchannel represents the number of virtual receiving channels, Nchirp represents the number of chirps sent by the radar in one frame, and X1 array is the coherent accumulation result, abs(.) means taking the absolute value;

[0020] Furthermore, the Doppler peak detection includes constant false alarm rate detection or findpeaks function detection. The constant false alarm rate detection is specifically as follows: detecting the target peak, recording all detected peaks and their peak positions idx, recorded as a set pks_location=[peaks location], and the number of peaks is recorded as Npks; the findpeaks function detection is specifically as follows: after the findpeaks function is executed, the peaks and their positions are sorted from large to small according to the peak size, and the peaks and their positions of the first N sizes are stored in the pks_location set matrix.

[0021] Furthermore, the conversion of the Doppler peak position into the Doppler phase shift is specifically:

[0022]

[0023] Where location i is the position corresponding to the i-th peak, and Ntx is the interval between the two values ​​before and after the chirp dimension in the X1 matrix, which is NTx chirp cycles sent by the radar.

[0024] Furthermore, the weights are allocated according to the pks of different peak values ​​and the sum is calculated as follows:

[0025]

[0026] in,

[0027] Furthermore, the construction process of the compensation matrix is ​​specifically as follows:

[0028]

[0029] The resulting Doppler compensation matrix doppler_comp_matrix has a size of Nchannel*Nchirp.

[0030] Furthermore, the compensation of the data matrix according to the compensation matrix is ​​specifically: dot-multiplying the data matrix X1 and the compensation matrix doppler_comp_matrix to obtain the compensated data matrix X1_comp:

[0031] X1_comp=X1·doppler_comp_matrix.

[0033] On the other hand, the present specification provides a device for extracting a millimeter-wave radar range-azimuth map, comprising a memory and one or more processors, wherein the memory stores executable code, and when the processor executes the executable code, the method for extracting a millimeter-wave radar range-azimuth map is implemented.

[0034] On the other hand, the present specification provides a computer-readable storage medium having a program stored thereon, and when the program is executed by a processor, the method for extracting a millimeter-wave radar range and azimuth map is implemented.

[0035] Beneficial effects:

[0036] The present invention optimizes the MVDR process, performs Doppler compensation in a multi-target environment, and eliminates the impact of target Doppler on the RA diagram, such as angle estimation errors and the expansion of the target size on the RA diagram. The RA diagram obtained by the present invention has higher angle accuracy; the target peak beam is narrower, and the expansion in the distance dimension and the angle dimension is smaller; the target peak energy value is larger, and the signal-to-noise ratio is higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart of a method for extracting a millimeter wave radar range and azimuth map provided by an embodiment of the present invention;

[0038] Figure 2 is the RA diagram obtained using the conventional method;

[0039] Figure 3 The RA graph obtained by the method provided in the embodiment of the present invention;

[0040] Figure 4 A schematic diagram of a device for extracting a millimeter-wave radar range-azimuth map provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The specific implementation modes of the present invention are further described in detail below with reference to the accompanying drawings.

[0042] like Figure 1 As shown, the specific steps of a method for extracting a millimeter wave radar range azimuth map include:

[0043] S1. Traverse each distance unit in the millimeter wave radar to obtain a data matrix, the size of which is obtained by the number of virtual receiving channels and the chirp sent by the radar in one frame;

[0044] Specifically, in this embodiment, this step includes: extracting the data matrix X1: traversing each range bin (distance unit), extracting the data matrix X1 of Nchannel*Nchirp size from the 1dfft radarcube (the radar data matrix that has undergone fast Fourier transform in the distance dimension), where Nchannel represents the number of virtual receiving channels (if there are 3 Tx, 4 Rx, and time division modulation is performed, there are a total of 3*4=12 virtual receiving channels), and Nchirp represents the number of chirps sent by the radar in one frame (a waveform sent once by the fmcw millimeter wave radar is called a chirp).

[0045] S2, coherently accumulate the data matrix along the dimension of the virtual receiving channel, then perform Fourier transform of the chirp dimension and take the absolute value to obtain the Doppler dimension spectrum absolute value sequence;

[0046] Specifically, in this embodiment, the step includes: performing coherent accumulation on X1 along the channel dimension, and then performing FFT on the chirp dimension, taking the absolute value of the result to obtain a Doppler dimension spectrum absolute value sequence X1_fft_abs.

[0047]

[0048] X1_fft_abs=abs(fft(X1 array ,Nfft))

[0049] Where Nfft represents the number of Doppler fast Fourier transform points, which is generally consistent with the Nchirp number, or is the smallest power of 2 (or 4, depending on whether the fast Fourier transform is radix 2 or radix 4) greater than Nchirp.

[0050] S3, performing Doppler peak detection on the Doppler dimension spectrum absolute value sequence to obtain the Doppler peak position;

[0051] Specifically, in this embodiment, the step includes: performing CFAR (Constant False Alarm Rate Detector) detection on X1_fft_abs, detecting the target peak, recording all detected peaks and their peak positions idx, recorded as a set pks_location=[peaks location], and the number of peaks is recorded as Npks. Since CFAR is a commonly used algorithm, it is used here to detect the peak in the X1_fft_abs signal and will not be described in detail.

[0052] Optionally, the findpeaks function (find peaks, detect whether a value in the sequence is greater than the two values ​​before and after it, if so, detect it as a peak) can be used instead of CFAR. After the findpeaks function is executed, the peaks and their positions are sorted from large to small according to the peak size, and the first N peaks and their positions are stored in the pks_location collection matrix. The number N can be selected according to the empirical value, generally 1 or 2. If it is 1, it means that the same distance and speed in the radar target are ignored. Among them, pks refers to the size of the peak contained in the Doppler spectrum absolute value sequence obtained after the previous findpeaks function is executed, location represents the peak position index value, and pks is the peak intensity (amplitude) corresponding to each index value;

[0053] pks_location=[peaks location]

[0054] peaks={pks1,pks2,…pks Npks}

[0055] location={location1,location2,…location Npks}

[0056] S4, converting the Doppler peak position into the Doppler phase shift, assigning weights according to the pks sizes of different peaks and calculating the sum, obtaining the Doppler peak phase compensation value, normalizing the Doppler peak phase compensation value and constructing the corresponding compensation matrix according to the size of the data matrix;

[0057] Specifically, in this embodiment, the step includes: converting the Doppler peak position into a Doppler phase shift:

[0058]

[0059] The denominator of the formula for calculating the phase shift includes Ntx. This is because in TDM modulation mode, Tx is sent in time, and multiple virtual receiving channels are virtualized in X1. Therefore, the two values ​​before and after the chirp dimension in the X1 matrix are actually separated by NTx chirp cycles sent by the radar, so it is necessary to divide by Ntx here. After obtaining the phase shift generated by each Doppler peak, the weights are assigned according to the pks size of different peaks and their sum is calculated as follows:

[0060]

[0061] Normalize pks_phase_comp as follows:

[0062]

[0063] comp_fai is the phase value of the normalized Doppler-phase compensation value doppler_comp

[0064] After normalization, the corresponding compensation matrix doppler_comp_matrix is ​​constructed according to the size of X1 as follows:

[0065]

[0066] The size of the obtained Doppler compensation matrix doppler_comp_matrix is ​​Nchannel*Nchirp, where doppler_comp_array is the compensation array, NRx means the number of receiving antenna units, and NTx*NRx is Nchannel, the number of receiving channels.

[0067] S5. Compensate the data matrix according to the compensation matrix, calculate the data noise defense difference according to the compensated data matrix, traverse each angle to calculate the steering vector, calculate the response of the MVDR filter at each angle, and integrate the results into the millimeter wave radar range and azimuth map.

[0068] Specifically, compensating the data matrix according to the compensation matrix includes: performing a dot multiplication of X1 and doppler_comp_matrix to obtain the compensated X1_comp:

[0069] X1_comp=X1·doppler_comp_matrix

[0070] After compensation, the subsequent steps of the MVDR algorithm are executed to obtain the RA graph: The subsequent steps of the MVDR algorithm include using X1_comp to calculate the data noise covariance R, traversing each angle to calculate the steering vector SteeringVector, calculating the response of the MVDR filter at each angle, and integrating the results into a RA graph of size Nrangebin*Nazimuthstep, where Nrangebin is the number of radar range bins and Nazimuthstep is the number of angles traversed in this step. Since the subsequent steps of the MVDR are common processing methods, they are not described here.

[0071] When using common methods such as MVDR and MUSIC to generate RA diagrams, since it is necessary to obtain data from multiple chirps to construct the data noise covariance matrix, errors caused by the target Doppler will be introduced.

[0072] Simulation is used to illustrate the difference between the RA diagram generated by the proposed method and the RA diagram generated by the conventional method. The simulation conditions are:

[0073]

[0074]

[0075] Set two point targets, and their point cloud information is:

[0076] Goal 1 Goal 2 Distance(m) 50m 60m Doppler(m / s) 1.3950m / s 4.1850m / s Horizontal angle (deg) 12.7311° -12.7311°

[0077] The RA diagram obtained by conventional methods is as follows Figure 2 As shown:

[0078] The distance azimuths corresponding to the two target peaks are:

[0079] Goal 1 Goal 2 Distance(m) 50.7031m 60.1563m Horizontal angle (deg) 14° -10°

[0080] Using the method described in this proposal, after Doppler compensation, the RA diagram is obtained as follows Figure 3 As shown:

[0081] The distance azimuths corresponding to the two target peaks are:

[0082] Goal 1 Goal 2 Distance(m) 49.8438m 60.1563m Horizontal angle (deg) 13° -13°

[0083] Corresponding to the above-mentioned embodiment of a method for extracting a millimeter-wave radar range-azimuth map, the present invention also provides an embodiment of a device for extracting a millimeter-wave radar range-azimuth map.

[0084] See also Figure 4 A millimeter-wave radar range-azimuth map extraction device provided in an embodiment of the present invention includes a memory and one or more processors, wherein the memory stores executable code, and when the processor executes the executable code, it is used to implement a millimeter-wave radar range-azimuth map extraction method in the above embodiment.

[0085] An embodiment of a millimeter-wave radar range-azimuth map extraction device provided by the present invention can be applied to any device with data processing capabilities, and the device with data processing capabilities can be a device or apparatus such as a computer. The device embodiment can be implemented through software, or through hardware or a combination of software and hardware. Taking software implementation as an example, as a device in a logical sense, it is formed by the processor of any device with data processing capabilities in which it is located reading the corresponding computer program instructions in the non-volatile memory into the internal memory for execution. From a hardware perspective, if Figure 4 As shown, it is a hardware structure diagram of any device with data processing capability where a millimeter wave radar range azimuth map extraction device provided by the present invention is located, except Figure 4In addition to the processor, memory, network interface, and non-volatile memory shown, any device with data processing capabilities in which the apparatus in the embodiments is located may also include other hardware, generally based on the actual functions of the device with data processing capabilities, which will not be described in detail.

[0086] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0087] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of the present invention. Ordinary technicians in this field can understand and implement it without paying creative work.

[0088] An embodiment of the present invention further provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, a method for extracting a millimeter-wave radar range-azimuth map in the above embodiment is implemented.

[0089] The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device of any device with data processing capability, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capability. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or is to be output.

[0090] The present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method for extracting a millimeter-wave radar range and azimuth map is implemented.

[0091] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0092] It should be understood that the above general description and the detailed description below are only exemplary and explanatory and cannot limit the present application. The present application is not limited to the precise structure described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present application is limited only by the attached claims.

Claims

1. A method for extracting a millimeter wave radar range and azimuth map, characterized in that: The method includes: S1. Traverse each distance unit in the millimeter wave radar to obtain a data matrix, the size of which is obtained by the number of virtual receiving channels and the chirp sent by the radar in one frame; S2, coherently accumulate the data matrix along the dimension of the virtual receiving channel, then perform Fourier transform of the chirp dimension and take the absolute value to obtain the Doppler dimension spectrum absolute value sequence; S3, performing Doppler peak detection on the Doppler dimension spectrum absolute value sequence to obtain the Doppler peak position; S4, converting the Doppler peak position into the Doppler phase shift, assigning weights according to the pks sizes of different peaks and calculating the sum, obtaining the Doppler peak phase compensation value, normalizing the Doppler peak phase compensation value and constructing the corresponding compensation matrix according to the size of the data matrix; S5. Compensate the data matrix according to the compensation matrix, calculate the data noise defense difference according to the compensated data matrix, traverse each angle to calculate the steering vector, calculate the response of the MVDR filter at each angle, and integrate the results into the millimeter wave radar range and azimuth map.

2. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The extraction of the data matrix specifically includes: traversing each distance unit, extracting a data matrix X1 of size Nchannel*Nchirp from the radar data matrix that has undergone a fast Fourier transform in the distance dimension, where Nchannel represents the number of virtual receiving channels, and Nchirp represents the number of chirps sent by the radar in one frame.

3. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The specific steps in S2 are: X1_fft_abs=abs(fft(X1 array ,Nfft)) Where Nfft represents the number of Doppler fast Fourier transform points, X1 is the extracted data matrix, Nchannel represents the number of virtual receiving channels, Nchirp represents the number of chirps sent by the radar in one frame, and X1 array It is the coherent accumulation result, and abs(.) means taking the absolute value.

4. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The Doppler peak detection includes constant false alarm rate detection or findpeaks function detection. The constant false alarm rate detection is specifically as follows: detecting the target peak, recording all detected peaks and their peak positions idx, recorded as a set pks_location=[peakslocation], and the number of peaks is recorded as Npks; the findpeaks function detection is specifically as follows: after the findpeaks function is executed, the peaks and their positions are sorted from large to small according to the peak size, and the peaks and their positions of the first N sizes are stored in the pks_location set matrix.

5. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The conversion of the Doppler peak position into the Doppler phase shift is specifically: Among them, Npks is the number of Doppler peaks, Nfft is the number of Doppler fast Fourier transform points, and location i is the position corresponding to the i-th peak, and Ntx is the interval between the two values ​​before and after the chirp dimension in the X1 matrix, which is NTx chirp cycles sent by the radar.

6. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The weights are allocated according to the pks values ​​of different peaks and the sum is calculated to obtain the Doppler peak phase compensation value: Among them, Npks is the number of Doppler peaks, pksphase i is the Doppler phase shift.

7. The method for extracting a millimeter wave radar range-azimuth map according to claim 6, characterized in that: The construction of the compensation matrix includes: The Doppler compensation array is: Where NRx means the number of receiving antenna units, NTx*NRx means the number of receiving channels Nchannel; According to the Doppler compensation array, the Doppler compensation matrix is ​​obtained as follows: The size of the obtained Doppler compensation matrix doppler_comp_matrix is ​​Nchannel*Nchirp, where Nchirp represents the number of chirps sent by the radar in one frame.

8. The method for extracting a millimeter wave radar range-azimuth map according to claim 1, characterized in that: The specific method of compensating the data matrix according to the compensation matrix is ​​as follows: dot multiplication of the data matrix X1 and the compensation matrix doppler_comp_matrix to obtain the compensated data matrix X1_comp: X1_comp=X1·doppler_comp_matrix.

9. A device for extracting a millimeter wave radar range and azimuth map, comprising a memory and one or more processors, wherein the memory stores executable code, characterized in that: When the processor executes the executable code, a method for extracting a millimeter-wave radar range-azimuth map according to any one of claims 1 to 8 is implemented.

10. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, a method for extracting a millimeter-wave radar range-azimuth map as described in any one of claims 1 to 8 is implemented.

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