CN114690140A

CN114690140A - Speed deblurring method and device, electronic equipment and storage medium

Info

Publication number: CN114690140A
Application number: CN202011567962.7A
Authority: CN
Inventors: 李文荣
Original assignee: Hangzhou Hikvision Digital Technology Co Ltd
Current assignee: Hangzhou Hikvision Digital Technology Co Ltd
Priority date: 2020-12-25
Filing date: 2020-12-25
Publication date: 2022-07-01

Abstract

The embodiment of the application provides a speed deblurring method, a speed deblurring device, electronic equipment and a storage medium, wherein objects are associated by combining CFAR two-dimensional masks of multi-frame radar signals, and the motion direction and possible speed value set of the objects can be estimated. Based on the estimated target motion direction and speed value set, removing part of MIMO compensation modes to obtain the rest MIMO preprocessing compensation modes; when the MIMO algorithm is processed, the optimal MIMO compensation mode can be obtained only by traversing the rest MIMO compensation modes, the algorithm operation complexity can be simplified, and the MIMO ambiguity resolution accuracy can be increased. And the performance loss caused by target speed and azimuth mutation caused by MIMO compensation errors is greatly reduced, and the target detection is improved while the target false detection is reduced. Especially in a target congestion scene, the performance is more remarkable.

Description

Speed deblurring method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of radar signal processing technologies, and in particular, to a speed ambiguity resolution method and apparatus, an electronic device, and a storage medium.

Background

The current millimeter wave radar antenna generally adopts a TDM (Time-division multiplexing) -MIMO (Multiple In Multiple Out) form, and the actual size of the antenna is effectively reduced through a virtual array element, so as to obtain a high-resolution target angle measurement result similar to a large-size antenna. Assume that a TDM-MIMO radar includes M transmit antennas and N receive antennas. By reasonably designing the spacing between the transmitting antennas and the spacing between the receiving antennas, the effect of 1 transmitting M × N receiving can be achieved. Assume that the distance between adjacent transmitting antennas is D and the distance between adjacent receiving antennas is D. In order to ensure that no antenna grating lobe occurs, d is generally required to be less than or equal to 0.5 lambda, wherein lambda is the radar wavelength. In order to maximize the utilization of the antenna aperture, the design generally needs to satisfy D ═ Nd.

Taking an FMCW (Frequency Modulated Continuous Wave) signal system with 2 transmitting antennas and 4 receiving antennas as an example, where D is 0.5 λ and D is 2 λ, the obtained TDM-MIMO radar virtual array element schematic diagram is shown in fig. 1, where virtual antenna represents virtual antenna and real antenna represents real antenna. Due to the fact that the TDM-MIMO radar adopts the working form of alternately transmitting signals by a plurality of transmitting antennas, two problems exist: firstly, the phase variation caused by the Doppler frequency of the moving target in the switching time of different transmitting antennas is coupled to each receiving antenna, so that the correct synthesis of the aperture of the receiving antenna is influenced; secondly, the TDM reduces the sampling rate in a slow time, so that the unambiguous velocity measurement range is significantly reduced, and once the velocity ambiguity occurs, the deviation of angle measurement is further caused. Therefore, how to carry out the speed ambiguity resolution method for the TDM-MIMO radar becomes the problem to be solved urgently.

Disclosure of Invention

An object of the embodiments of the present application is to provide a speed ambiguity resolving method, apparatus, electronic device and storage medium, so as to implement speed ambiguity resolution for a TDM-MIMO radar. The specific technical scheme is as follows:

in a first aspect, an embodiment of the present application provides a speed deblurring method, where the method includes:

acquiring multiple frames of radar signals, and respectively determining a power diagram of each frame of radar signal;

respectively mapping each power map to a two-dimensional matrix of a distance dimension and a Doppler dimension to obtain a constant false alarm rate CFAR two-dimensional mask of each frame of radar signal;

according to the time sequence of each frame of radar signal, carrying out track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the estimated motion speed and the estimated motion direction of each object;

aiming at each object, selecting a preprocessing MIMO compensation mode of the object from preset MIMO compensation modes according to the estimated motion speed and the estimated motion direction of the object;

and traversing each MIMO compensation mode in the preprocessing MIMO compensation modes of the object aiming at each object to obtain a target MIMO compensation mode, and acquiring a speed ambiguity resolution result of the object in the target MIMO compensation mode, wherein the speed ambiguity resolution result of the object comprises the real speed and the real azimuth of the object.

In a possible implementation, the acquiring multiple frames of radar signals and determining the power map of each frame of radar signals respectively includes:

acquiring analog-to-digital converter (ADC) data of each channel of the radar virtual antenna array to obtain multi-frame radar signals;

respectively carrying out two-dimensional fast Fourier transform on ADC data of each channel in each frame of radar signal to obtain a virtual array vector of each frame of radar signal;

and respectively carrying out non-coherent accumulation on the virtual array vector of each frame of radar signal to obtain a power diagram of each frame of radar signal.

In a possible implementation manner, the mapping each of the power maps to a two-dimensional matrix in a range dimension and a doppler dimension to obtain a constant false alarm rate CFAR two-dimensional mask of each frame of radar signal includes:

carrying out CFAR detection on each power diagram to obtain a noise intensity threshold of the power diagram;

and aiming at each power map, in a two-dimensional matrix of a distance dimension and a Doppler dimension, setting the power which is larger than the noise intensity threshold of the power map in the power map as a first numerical value, and setting the power which is not larger than the noise intensity threshold of the power map in the power map as a second numerical value to obtain a CFAR two-dimensional mask of the radar signal corresponding to the power map, wherein the area corresponding to the first numerical value contains an object, and the area corresponding to the second numerical value does not contain the object.

In a possible implementation manner, the performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal to obtain an estimated motion speed and an estimated motion direction of each object respectively includes:

performing connected domain analysis on each CFAR two-dimensional mask to obtain target information of each object in each CFAR two-dimensional mask, wherein the target information of the object comprises the object width, the object height and the object center coordinate of the object aiming at any object;

according to the time sequence of each frame of radar signal and the target information of each object, performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the motion track of each object;

and respectively determining the estimated motion speed and the estimated motion direction of each object at least according to the motion track of each object and the time difference between each frame of radar signal.

In a possible embodiment, said selecting, for each object, a pre-processing MIMO compensation mode of the object from the preset MIMO compensation modes according to the estimated motion velocity and the estimated motion direction of the object includes:

aiming at each object, acquiring the motion direction and the motion speed of the object under each compensation mode in preset MIMO compensation modes;

aiming at each object, selecting a compensation mode with the motion direction being the same as the estimated motion direction of the object from preset MIMO compensation modes to obtain a compensation mode after the object is filtered;

and aiming at each object, selecting a compensation mode with the error between the motion speed and the estimated motion speed of the object within a preset range from the compensation modes after the object is filtered, so as to obtain a preprocessing MIMO compensation mode of the object.

In a second aspect, an embodiment of the present application provides a speed deblurring apparatus, including:

the power diagram acquisition unit is used for acquiring multiple frames of radar signals and respectively determining the power diagram of each frame of radar signal;

the CFAR detection unit is used for mapping each power map to a two-dimensional matrix of a distance dimension and a Doppler dimension respectively to obtain a CFAR two-dimensional mask of each frame of radar signal;

the motion estimation unit is used for performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal to respectively obtain the estimated motion speed and the estimated motion direction of each object;

the compensation mode removing unit is used for selecting a preprocessing MIMO compensation mode of each object from preset MIMO compensation modes according to the estimated motion speed and the estimated motion direction of the object;

and the speed ambiguity resolving unit is used for traversing each MIMO compensation mode in the preprocessing MIMO compensation modes of the object aiming at each object to obtain a target MIMO compensation mode and acquiring a speed ambiguity resolving result of the object under the target MIMO compensation mode, wherein the speed ambiguity resolving result of the object comprises the real speed and the real orientation of the object.

In a possible implementation manner, the power map obtaining unit is specifically configured to: acquiring analog-digital converter (ADC) data of each channel of the radar virtual antenna array to obtain multi-frame radar signals; respectively carrying out two-dimensional fast Fourier transform on ADC data of each channel in each frame of radar signal to obtain a virtual array vector of each frame of radar signal; and respectively carrying out non-coherent accumulation on the virtual array vector of each frame of radar signal to obtain a power diagram of each frame of radar signal.

In a possible implementation manner, the CFAR detection unit is specifically configured to: carrying out CFAR detection on each power diagram to obtain a noise intensity threshold of the power diagram; and aiming at each power map, in a two-dimensional matrix of a distance dimension and a Doppler dimension, setting the power which is larger than the noise intensity threshold of the power map in the power map as a first numerical value, and setting the power which is not larger than the noise intensity threshold of the power map in the power map as a second numerical value to obtain a CFAR two-dimensional mask of the radar signal corresponding to the power map, wherein the area corresponding to the first numerical value contains an object, and the area corresponding to the second numerical value does not contain the object.

In a possible implementation, the motion estimation unit is specifically configured to: performing connected domain analysis on each CFAR two-dimensional mask to obtain target information of each object in each CFAR two-dimensional mask, wherein the target information of the object comprises the object width, the object height and the object center coordinate of the object aiming at any object; according to the time sequence of each frame of radar signal and the target information of each object, performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the motion track of each object; and respectively determining the estimated motion speed and the estimated motion direction of each object at least according to the motion track of each object and the time difference between each frame of radar signal.

In a possible implementation manner, the compensation mode rejection unit is specifically configured to: aiming at each object, acquiring the motion direction and the motion speed of the object under each compensation mode in preset MIMO compensation modes; aiming at each object, selecting a compensation mode with the motion direction being the same as the estimated motion direction of the object from preset MIMO compensation modes to obtain a compensation mode after the object is filtered; and aiming at each object, selecting a compensation mode with the error between the motion speed and the estimated motion speed of the object within a preset range from the compensation modes after the object is filtered, so as to obtain a preprocessing MIMO compensation mode of the object.

In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory;

the memory is used for storing a computer program;

the processor is configured to implement any of the speed deblurring methods of the present application when executing the program stored in the memory.

In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements any of the speed deblurring methods described in the present application.

The embodiment of the application has the following beneficial effects:

the speed deblurring method, the speed deblurring device, the electronic equipment and the storage medium provided by the embodiment of the application are combined with the CFAR two-dimensional mask of the multi-frame radar signal to associate the object, so that the motion direction and the possible speed value set of the object can be estimated. Based on the estimated target motion direction and speed value set, removing part of MIMO compensation modes to obtain the rest MIMO preprocessing compensation modes; when the MIMO algorithm is processed, the optimal MIMO compensation mode can be obtained only by traversing the rest MIMO compensation modes, the algorithm operation complexity can be simplified, and the MIMO ambiguity resolution accuracy can be increased. And the performance loss caused by target speed and azimuth mutation caused by MIMO compensation errors is greatly reduced, and the target detection is improved while the target false detection is reduced. Especially in a target congestion scene, the performance is more remarkable. Of course, not all advantages described above need to be achieved at the same time in the practice of any one product or method of the present application.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic diagram of a virtual array element of a MIMO radar in the related art;

FIG. 2 is a schematic diagram of the operation of the speed deblurring system of the embodiment of the present application;

FIG. 3 is a schematic diagram of a CFAR two-dimensional mask according to an embodiment of the present disclosure;

FIG. 4 is a schematic diagram of object trajectory association according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a velocity deblurring method according to an embodiment of the present application;

fig. 6 is a schematic diagram of a specific implementation manner of step S103 in the embodiment of the present application;

fig. 7 is a schematic diagram of a specific implementation manner of step S104 in the embodiment of the present application;

FIG. 8 is a schematic diagram of a speed deblurring apparatus according to an embodiment of the present application;

fig. 9 is a schematic diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

First, terms in the present application are explained.

Radar: an electronic apparatus for detecting an object using electromagnetic waves. The radar irradiates a target by transmitting an electromagnetic wave and receives an echo thereof, thereby obtaining information such as a distance, a distance change rate (radial velocity), an azimuth, and an altitude from the target to an electromagnetic wave transmission point.

MIMO (Multiple In Multiple Out, Multiple input Multiple output) radar: multiple-input multiple-output radar is a technique to improve the radar angle estimation capability. There are mainly FDM (Frequency Division Multiplexing), CDM (Code Division Multiplexing), and TDM (Time-Division Multiplexing). In consideration of cost limitation and implementation complexity of semiconductor devices, the current millimeter wave radar basically adopts TDM-MIMO technology. In the present application, MIMO refers to TDM-MIMO unless otherwise specified.

Speed blurring: the phenomenon of real speed of the target is difficult to distinguish due to the confusion of the speed of the measured target caused by the frequency spectrum aliasing phenomenon. Especially, the TDM-MIMO radar reduces the sampling rate in slow time, so that the unambiguous speed measurement range is obviously reduced, and the speed ambiguity problem is easy to occur.

The current millimeter wave radar antenna generally adopts a TDM (Time-division multiplexing) -MIMO (Multiple In Multiple Out) form, and the actual size of the antenna is effectively reduced through a virtual array element, so as to obtain a high-resolution target angle measurement result similar to a large-size antenna. Assume a TDM-MIMO radar includes M transmit antennas and N receive antennas. By reasonably designing the spacing between the transmitting antennas and the spacing between the receiving antennas, the effect of 1 transmitting M × N receiving can be achieved. Assume that the spacing between adjacent transmit antennas is D and the spacing between adjacent receive antennas is D. In order to ensure that no antenna grating lobe occurs, d is generally required to be less than or equal to 0.5 lambda, wherein lambda is the radar wavelength. In order to maximize the utilization of the antenna aperture, the design generally needs to satisfy D ═ Nd.

Taking an FMCW (Frequency Modulated Continuous Wave) signal system with 2 transmitting antennas and 4 receiving antennas as an example, where D is 0.5 λ and D is 2 λ, the schematic diagram of the obtained TDM-MIMO radar virtual array element is shown in fig. 1. Due to the fact that the TDM-MIMO radar adopts the working mode that the multiple transmitting antennas alternately transmit signals, two problems exist: firstly, the phase variation caused by the Doppler frequency of the moving target in different transmitting antenna switching time can be coupled to each receiving antenna, and the correct synthesis of the aperture of the receiving antenna is influenced; secondly, the TDM reduces the sampling rate in a slow time, so that the unambiguous velocity measurement range is significantly reduced, and once the velocity ambiguity occurs, the deviation of angle measurement is further caused. Therefore, the TDM-MIMO radar in the prior art has high measurement error.

In the related art, in order to increase the accuracy of the TDM-MIMO radar, the following compensation method is adopted for speed ambiguity resolution:

step 1: estimating a velocity-induced phase shift of a virtual array element vector S of a signal

Velocity induced phase shift

With the true speed v of the target_trueAnd (4) correlating. Power map estimated velocity v obtained based on power map_estThere may be velocity ambiguity, so the target true velocity v_trueThe value is unknown, but the possible value set, v, can be obtained by estimating the speed from the power map_true∈{v_est,v_est+2v_max,v_est-2v_maxIn which v is_maxThe maximum unambiguous measurement speed is obtained. It is emphasized that the relation between the real speed and the estimated speed of the power diagram is v_true＝v_est+2xv_maxAnd x belongs to R, the value of x is {0,1, -1} aiming at the practical application scene, so that the requirement can be met, and the value of x in the MIMO algorithm is limited by a transmitting antenna.

Taking different speeds as values v_est,v_est+2v_max,v_est-2v_maxThe obtained velocity-induced phase shifts are respectively called compensation mode 0, compensation mode 1 and compensation mode 2, and the values are respectively

And

in step 1, the calculation formula relationship existing among the symbols is as follows:

estimated velocity v_est: and directly calculating and obtaining based on the power diagram.

True velocity v_trueAnd the estimated velocity v_estThe relationship is as follows:

v_true∈{v_est,v_est+2v_max,v_est-2v_max}

velocity induced phase shift

Maximum velocity v_max：

Wherein λ is radar wavelength, T_cOne chirp period. As shown in FIG. 1, T is the number of transmit antennas in the case of 2 transmit antennas_c＝2T。

Step 2: use of

Correcting the phase of each element of the virtual array vector S to obtain a corrected virtual array vector S_c. Based on different compensation modes, obtaining corresponding corrected virtual array vector S_c0，S_c1And S_c2。

In step 2, the calculation formula relationship existing among the symbols is as follows:

virtual array vector S:

rectified virtual array vector S_c：

If it is

If the correction is correct, then

To obtain S_cThe formula is as follows:

wherein,

the phase caused by the path difference of adjacent receiving antennas,

theta is the azimuth of the target, d is the spacing between adjacent receiving antennas, and lambda is the radar wavelength.

The phase variation of the target Doppler frequency in the switching time of the adjacent transmitting antenna is brought. S_mnThe discrete digital signal of the echo signal transmitted by the mth transmitting antenna and received by the nth receiving antenna is transformed by Fast Fourier Transform (FFT) to obtain a signal.

And step 3: for the corrected virtual array vector S_cPerforming a first Fourier transform to generate a corrected virtual array spectrum P_c. Different compensation modes are adopted to obtain corresponding virtual array spectrum P_c0，P_c1And P_c2。

And 4, step 4: and obtaining an optimal compensation mode according to the corrected virtual array spectrum. Theoretically, the compensation mode corresponding to the array spectrum with the highest peak value is the optimal compensation mode.

And 5: and obtaining the target speed and the target direction. The speed and the direction obtained by the optimal compensation mode are the target speed and the direction finally obtained by the target.

However, due to various factors such as noise disturbance and hardware errors, a certain error rate, which is close to 10%, exists when the algorithm performs speed deblurring, and an error compensation mode causes the speed and the azimuth of the output target point cloud to be abnormal. The TDM-MIMO compensation modes of the same target at different moments (different frames) are mutually independent and different, and are represented as time variation, the speed of the same target is constantly changed, the target direction jitter is large, so that the target tracking is influenced, performance indexes such as detection and false detection are reduced, and particularly in a congestion scene, the phenomenon is more remarkable.

The inventor finds that the data cannot be optimized aiming at single-frame data due to disturbance of the data; the relevance between time domain multiframes undoubtedly provides an additional decision characteristic for TDM-MIMO speed ambiguity resolution. Specifically, the target is associated by combining a radar multi-frame CFAR (Constant False-Alarm Rate) detection result, and the moving direction of the target and a possible speed value set can be estimated. Thereby excluding part of TDM-MIMO compensation phase mode and further increasing the TDM-MIMO de-ambiguity correct probability. In view of this, an embodiment of the present application provides a speed deblurring system, including: the device comprises a power diagram acquisition module, a CFAR detection module, an MIMO mode preprocessing module, a DOA (Direction Of Arrival) estimation module and a cluster tracking module.

As shown in fig. 2, the input of the whole system is ADC (Analog to Digital Converter) data of the radar, and the output is final target trajectory list information. The system is also a currently general radar target detection + tracking algorithm framework, and each module of the speed ambiguity resolving system is described in detail below.

A power map acquisition module: the input is ADC data and the output is a radar power map. ADC data of each channel of the virtual antenna array is respectively subjected to two-dimensional FFT (Fast Fourier Transform), and then a power diagram is obtained through non-coherent accumulation.

CFAR detection module: the input is a power map, and the output is a set of detected target points, represented by a binarized CFAR two-dimensional mask. A CFAR two-dimensional mask of a set of possible target points may be as shown in fig. 3, where the abscissa is the Doppler dimension and the ordinate is the Range dimension. A threshold is determined after processing noise in the input power diagram, and the threshold is compared with each signal point of the power diagram. If the input signal exceeds the threshold, judging that a target exists; otherwise, the target is judged to be not available.

A MIMO mode pre-processing module: aiming at the CFAR two-dimensional mask, the detected targets are represented as bright spots, and the targets are associated based on time-domain multi-frames, so that the motion track of the targets in the Range-Doppler dimension can be obtained, wherein one frame corresponds to one CFAR two-dimensional mask. A schematic diagram of a possible time-domain multi-frame target association may be shown in fig. 4. Where dimension K represents the data frame number. After the motion trail of the target in the Range-Doppler dimension is obtained, the MIMO compensation mode of the target can be pre-screened. The screening process is as follows:

step 1: and performing connected domain analysis based on the output CFAR two-dimensional mask to obtain a target bright spot list of the current frame. The target bright spot list of the current frame comprises connected domain information of each bright spot in the current frame in the CFAR two-dimensional mask image, namely target information of the bright spot; for any bright spot, the target information of the bright spot may include information of a bright spot width, a bright spot height, a distance-doppler coordinate of a bright spot center, a signal-to-noise ratio, and the like of the bright spot.

Step 2: and performing track association based on the time domain accumulated multiframes. When the tracks are associated, processing can be performed based on an image tracking algorithm.

And step 3: and acquiring the motion direction of the target (far away from the radar or close to the radar) and the speed of the target based on the target association track. Based on CFAR two-dimensional mask, target estimated speed v can be obtained_estBut since there may be velocity ambiguity, the target true velocity v_trueThe value is unknown. And based on the information of target track displacement, inter-frame difference, frame rate and the like, accurate target speed information can be estimated.

And 4, step 4: and removing part of the MIMO compensation mode based on the target motion direction and the speed to obtain an MIMO preprocessing compensation mode.

And a DOA estimation module: and aiming at the CFAR detection point (bright spot), extracting each channel data in the virtual antenna array two-dimensional FFT to perform one-dimensional direction FFT processing, and acquiring the target direction of arrival. When the MIMO ambiguity resolution algorithm is adopted for processing, only the MIMO preprocessing compensation mode is traversed, and the optimal compensation mode, the corresponding speed and the corresponding direction information are selected from the MIMO preprocessing compensation mode.

A clustering tracking module: and clustering and tracking the CFAR detection points by adopting a related clustering and tracking algorithm. And during clustering, converging the target point cloud, and outputting information such as target speed, direction and the like. Tracking is generally divided into two major modules: firstly, starting a flight path to generate an initial track, and performing tracking processing after confirmation; and secondly, tracking track maintenance, including track updating, extrapolation, extinction processing and the like.

In the embodiment of the application, the objects are associated by combining CFAR two-dimensional masks of multiple radar signals, and the moving direction and possible speed value set of the objects can be estimated. Based on the estimated target motion direction and speed value set, removing part of MIMO compensation modes to obtain the rest MIMO preprocessing compensation modes; and when the MIMO algorithm is used for processing, only traversing the remaining MIMO compensation modes, and selecting the optimal MIMO compensation mode from the remaining MIMO compensation modes, thereby increasing the fuzzy accuracy of the MIMO solution.

The embodiment of the present application further provides a speed deblurring method, and referring to fig. 5, the method includes:

s101, obtaining multiple frames of radar signals, and respectively determining a power diagram of each frame of radar signal.

The speed ambiguity resolution method in the embodiment of the application can be implemented by an electronic device, and the electronic device can be a radar device, for example, a MIMO radar device, a device with a computing function connected to the radar device, and the like.

The method for obtaining the power map of the radar signal can be seen in a manner of obtaining the power map of the radar signal in the related art. In an embodiment, the obtaining multiple frames of radar signals and determining the power map of each frame of radar signals respectively includes:

step one, ADC data of each channel of the radar virtual antenna array is obtained, and multi-frame radar signals are obtained.

The discrete digital signal data output by the ADC of each channel of the radar virtual antenna array can be obtained, and multi-frame radar signals are obtained.

And step two, respectively carrying out two-dimensional fast Fourier transform on ADC data of each channel in each frame of radar signal to obtain a virtual array vector of each frame of radar signal.

The FFT conversion of ADC sampling sequence number dimensionality and sampling period dimensionality can be carried out on ADC data of each channel in each frame of radar signal, and a virtual array vector of each frame of radar signal is obtained.

And step three, respectively carrying out non-coherent accumulation on the virtual array vector of each frame of radar signal to obtain a power diagram of each frame of radar signal.

And S102, mapping each power map to a two-dimensional matrix of a distance dimension and a Doppler dimension to obtain a CFAR two-dimensional mask of each frame of radar signals.

The CFAR two-dimensional mask includes a distance dimension and a doppler dimension, and the CFAR two-dimensional mask may be binarized, for example, a region where an object exists may be represented by a first numerical value, and a region where an object does not exist may be represented by a second numerical value, where the object is an object detected by the radar. One possible CFAR two-dimensional mask may be as shown in fig. 3, where the abscissa is the doppler dimension and the ordinate is the distance dimension.

In a possible embodiment, the mapping each power map to a two-dimensional matrix in a range dimension and a doppler dimension to obtain a constant false alarm rate CFAR two-dimensional mask of each frame of radar signal includes:

and step A, carrying out CFAR detection on each power diagram to obtain the noise intensity threshold of the power diagram.

And step B, aiming at each power diagram, in a two-dimensional matrix of a distance dimension and a Doppler dimension, setting the power which is larger than the noise intensity threshold of the power diagram in the power diagram as a first numerical value, and setting the power which is not larger than the noise intensity threshold of the power diagram in the power diagram as a second numerical value, so as to obtain a CFAR two-dimensional mask of the radar signal corresponding to the power diagram, wherein the area corresponding to the first numerical value contains an object, and the area corresponding to the second numerical value does not contain the object. The area corresponding to the first numerical value of the CFAR two-dimensional mask indicates that an object exists at the actual position corresponding to the area, and the area corresponding to the second numerical value indicates that the object does not exist at the actual position corresponding to the area.

And S103, performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal, and respectively obtaining the estimated motion speed and the estimated motion direction of each object.

The same object in each CFAR two-dimensional mask can be tracked by using a target tracking algorithm in the related art, and the track of the same object is associated, so that the estimated motion speed and the estimated motion direction of each object are obtained.

S104, aiming at each object, selecting a preprocessing MIMO compensation mode of the object from preset MIMO compensation modes according to the estimated motion speed and the estimated motion direction of the object.

The preset MIMO compensation mode comprises a plurality of MIMO compensation modes, the MIMO compensation mode which does not meet the constraint conditions of the estimated motion speed and the estimated motion direction of the object is removed from the preset MIMO compensation mode aiming at any object, and the residual MIMO compensation mode in the preset MIMO compensation mode is used as the object preprocessing MIMO compensation mode. In one example, for any object, in the preset MIMO compensation mode, all compensation modes, in which an error between a motion speed and an estimated motion speed of the object is within a preset range and a motion direction is the same as an estimated motion direction of the object, are selected as the preprocessing MIMO compensation mode of the object.

S105, traversing each MIMO compensation mode in the preprocessing MIMO compensation modes of the object aiming at each object to obtain a target MIMO compensation mode, and acquiring a speed ambiguity resolution result of the object under the target MIMO compensation mode, wherein the speed ambiguity resolution result of the object comprises the real speed and the real orientation of the object.

And traversing each MIMO compensation mode in the pre-processing MIMO compensation modes to obtain an optimal MIMO compensation mode, namely a target MIMO compensation mode, calculating a speed ambiguity resolution result in the target MIMO compensation mode, and finally obtaining the speed and the direction of the object. The specific way of traversing each MIMO compensation mode in the pre-processing MIMO compensation modes to obtain the optimal MIMO compensation mode, i.e. the target MIMO compensation mode, may refer to the calculation way in the related art. In one embodiment, for each MIMO compensation mode in the pre-processing MIMO compensation modes, performing compensation correction on a virtual array vector by using the MIMO compensation mode to obtain a corrected virtual array vector in the MIMO compensation mode; for each MIMO compensation mode in the preprocessing MIMO compensation modes, carrying out Fourier transform on the virtual array vector corrected in the MIMO compensation mode to obtain a virtual array spectrum in the MIMO compensation mode; and determining a target MIMO compensation mode according to the virtual array spectrum under each MIMO compensation mode in the pre-processing MIMO compensation modes. In one example, the MIMO compensation mode corresponding to the virtual array spectrum having the highest peak value is set as the target MIMO compensation mode.

After the target MIMO compensation mode is obtained, the direction of arrival of the object in the target MIMO compensation mode, including distance information and azimuth information of the object, may be obtained. The actual movement speed and the actual movement direction of each object can be obtained by using the distance information and the azimuth information of the object in each frame of radar signal and adopting a clustering and tracking algorithm in the related technology. The tracking algorithm generally comprises two parts, wherein one part is that track starting is carried out to generate an initial track, and tracking processing can be carried out after confirmation; and secondly, tracking track maintenance, including track updating, extrapolation, extinction processing and the like.

In the embodiment of the application, the objects are associated by combining CFAR two-dimensional masks of multi-frame radar signals, and the moving direction and possible speed value set of the objects can be estimated. Based on the estimated target motion direction and speed value set, removing part of MIMO compensation modes to obtain the rest MIMO preprocessing compensation modes; when the MIMO algorithm is processed, the optimal MIMO compensation mode can be obtained only by traversing the rest MIMO compensation modes, the algorithm operation complexity can be simplified, and the MIMO ambiguity resolution accuracy can be increased. And the performance loss caused by target speed and azimuth mutation caused by MIMO compensation errors is greatly reduced, and the target detection is improved while the target false detection is reduced. Especially in a target congestion scene, the performance is more remarkable.

In a possible implementation manner, referring to fig. 6, the performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal to obtain the estimated motion speed and the estimated motion direction of each object respectively includes:

and step S1031, performing connected domain analysis on each CFAR two-dimensional mask to obtain target information of each object in each CFAR two-dimensional mask, where the target information of any object includes an object width, an object height, and an object center coordinate of the object.

Assuming that the first numerical value in the CFAR two-dimensional mask corresponds to white and the second numerical value corresponds to black, performing connected domain analysis on white (i.e., bright spots) in the CFAR two-dimensional mask, thereby obtaining connected domain information, i.e., target information, of each object in the CFAR two-dimensional mask. For any object, the target information of the object includes an object width, an object height, and object center coordinates of the object, that is, coordinates of the object center of the object in the distance dimension and the doppler dimension. In addition, the target information of the object may further include information such as a signal-to-noise ratio of the object.

And S1032, according to the time sequence of each frame of radar signal and the target information of each object, performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the motion track of each object.

For example, as shown in fig. 4, the same object is subjected to track association in time series, and the motion track of each object is obtained.

When the objects in the radar signal are sparse, for example, when the density (number in a unit space) of the objects is smaller than a preset density threshold, the motion track association reliability is high, and a large number of frames can be selected to associate each object to obtain the motion track of each object. When the objects are dense, for example, the density of the objects is greater than a preset density threshold, in order to reduce the situation of motion trajectory association error, the number of frames of the motion trajectory of each object obtained by association each time may be reduced, for example, the motion trajectory of each object is obtained by selecting two frames of radar signals each time and analyzing the radar signals.

And S1033, respectively determining the estimated motion speed and the estimated motion direction of each object at least according to the motion track of each object and the time difference between each frame of radar signal.

For any object, after obtaining the associated track of the object, the estimated motion speed and the estimated motion direction of the object can be calculated according to the time difference between the radar signals of each frame and the associated track of the object.

In one possible embodiment, referring to fig. 7, the above-mentioned selecting, for each object, a pre-processing MIMO compensation mode of the object from the preset MIMO compensation modes according to the estimated motion velocity and the estimated motion direction of the object includes:

s1041, for each object, obtaining a motion direction and a motion speed of the object in each compensation mode of the preset MIMO compensation modes.

The obtaining method of the motion direction and the motion speed of the object in each compensation mode in the preset MIMO compensation mode may refer to the obtaining method in the related art, and in one example, the maximum unambiguous measurement speed and the power map estimation speed of the object may be obtained, so as to calculate the motion direction and the motion speed of the object in each compensation mode.

In particular, a velocity-induced phase shift of a virtual array element vector S of a radar signal is estimated

Velocity induced phase shift

With the true speed v of the target_trueAnd (4) correlating. Power map estimated velocity v obtained based on power map_estThere may be velocity ambiguity, so the target true velocity v_trueThe value is unknown, but the possible value set, v, can be obtained by estimating the speed from the power map_true＝v_est+2*k*v_maxK is …, -1,0,1, …, wherein v is_maxFor maximum unambiguous measurement speed, k is an integer within a limited range, determined from the motion characteristics of the object (i.e. the range of possible motion speeds of the object). Generally, for practical application scenarios, for example, for scenarios where the object is an automobile, a pedestrian, a non-automobile, etc., the value of k is {0,1, -1}, and then v is_trueDifferent value is v_est,v_est+2v_max,v_est-2v_maxThe obtained velocity-induced phase shifts are referred to as compensation mode 0, compensation mode 1 and compensation mode 2, respectively, i.e. each of the preset MIMO compensation modes.

For example, the estimated speed of the power diagram is 8m/s, the maximum unambiguous velocity measurement range is-15 m/s to 15m/s, namely, the maximum unambiguous velocity measurement range is 15 m/s. For a vehicle object, k takes the value of-1, 0,1, and its speed may be-24, 8, 38. Under other k value conditions, for example, when k takes 2, the speed of the vehicle will reach 244.8 km/h, which is not in line with the motion characteristics of the vehicle.

S1042, for each object, selecting a compensation mode with a motion direction the same as the estimated motion direction of the object from the preset MIMO compensation modes to obtain a compensation mode after filtering the object.

For example, if the motion direction of the compensation pattern 0 is "-", the motion direction of the compensation pattern 1 is "+", and the motion direction of the compensation pattern 2 is "+", and the estimated motion directions of an object are "+", the filtered compensation patterns are the compensation pattern 1 and the compensation pattern 2. It is to be understood that "-" and "+" are predefined herein, and one direction may be set to "+" and the opposite direction may be set to "-".

S1043, aiming at each object, in the compensation modes after the object filtering, selecting the compensation mode of which the error between the motion speed and the estimated motion speed of the object is within a preset range to obtain the preprocessing MIMO compensation mode of the object.

The preset range can be customized according to actual conditions, and is set to be 20%, 40%, 60%, 80% or the like of the estimated movement speed. For example, the estimated moving speed of the object is 10m/s, and the preset range is 50% of the estimated moving speed, i.e., 5 m/s; the motion speed of the object in the compensation mode 1 in the filtered compensation mode is 8 m/s; the motion speed of the object in the compensation mode 2 is 38 m/s; the error between the motion velocity of the object and the estimated motion velocity in the compensation mode 1 is |8-10| ═ 2m/s, and the error between the motion velocity of the object and the estimated motion velocity in the compensation mode 2 is |38-10| ═ 28m/s, which are respectively compared with 5m/s, so that the error between the motion velocity of the object and the estimated motion velocity in the compensation mode 1 is within the preset range, and therefore the compensation mode 1 is selected as the pre-processing MIMO compensation mode.

Therefore, by the speed ambiguity resolution method, part of MIMO compensation modes can be eliminated, when the MIMO algorithm is processed, the optimal MIMO compensation mode can be obtained only by traversing the rest of the MIMO compensation modes, the complexity of the algorithm can be greatly simplified, and the speed ambiguity resolution efficiency is greatly improved while the MIMO ambiguity resolution accuracy is increased. And filtering is carried out in the passing motion direction and filtering is carried out in the passing motion speed, so that the number of compensation modes for calculating the speed error can be reduced, the calculation amount is reduced, and the speed deblurring efficiency can be improved.

The embodiment of the present application further provides a speed deblurring apparatus, referring to fig. 8, the apparatus includes:

the power diagram acquiring unit 11 is configured to acquire multiple frames of radar signals and respectively determine a power diagram of each frame of radar signal;

a CFAR detection unit 12, configured to map each power map to a two-dimensional matrix of a distance dimension and a doppler dimension, respectively, to obtain a CFAR two-dimensional mask of each frame of radar signal;

a motion estimation unit 13, configured to perform track association on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal, and obtain an estimated motion speed and an estimated motion direction of each object respectively;

a compensation mode removing unit 14, configured to select, for each object, a pre-processing MIMO compensation mode of the object from preset MIMO compensation modes according to the estimated motion speed and the estimated motion direction of the object;

and the speed deblurring unit 15 is configured to traverse, for each object, each MIMO compensation mode in the pre-processing MIMO compensation modes of the object to obtain a target MIMO compensation mode, and obtain a speed deblurring result of the object in the target MIMO compensation mode, where the speed deblurring result of the object includes a real speed and a real orientation of the object.

The power map obtaining unit 11 in the embodiment of the present application is equivalent to a power map obtaining module in the speed deblurring system; the CFAR detection unit 12 in the embodiment of the present application is equivalent to the CFAR detection module in the speed deblurring system; the motion estimation unit 13 and the compensation mode removing unit 14 in the embodiment of the present application are equivalent to the MIMO mode preprocessing module in the velocity deblurring system; the speed deblurring unit 15 in the embodiment of the present application is equivalent to the MIMO mode preprocessing module DOA estimation module and the cluster tracking module in the speed deblurring system.

In a possible implementation manner, the motion estimation unit is specifically configured to: performing connected domain analysis on each CFAR two-dimensional mask to obtain target information of each object in each CFAR two-dimensional mask, wherein the target information of each object comprises the object width, the object height and the object center coordinate of the object aiming at any object; according to the time sequence of each frame of radar signal and the target information of each object, performing track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the motion track of each object; and respectively determining the estimated motion speed and the estimated motion direction of each object according to the motion track of each object and the time difference between each frame of radar signal.

In a possible implementation manner, the compensation pattern rejection unit is specifically configured to: aiming at each object, acquiring the motion direction and the motion speed of the object under each compensation mode in preset MIMO compensation modes; aiming at each object, selecting a compensation mode with the motion direction being the same as the estimated motion direction of the object from preset MIMO compensation modes to obtain a compensation mode after the object is filtered; and aiming at each object, selecting a compensation mode with the error between the motion speed and the estimated motion speed of the object within a preset range from the compensation modes after the object is filtered, so as to obtain a preprocessing MIMO compensation mode of the object.

An embodiment of the present application further provides an electronic device, including: a processor and a memory;

the memory is used for storing computer programs;

the processor is configured to implement any of the speed deblurring methods described above when executing the computer program stored in the memory.

Optionally, referring to fig. 9, in addition to the processor 21 and the memory 23, the electronic device according to the embodiment of the present application further includes a communication interface 22 and a communication bus 24, where the processor 21, the communication interface 22, and the memory 23 complete mutual communication through the communication bus 24. Specifically, the electronic device in the embodiment of the present application may be a MIMO radar.

The communication bus mentioned in the electronic device may be a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this is not intended to represent only one bus or type of bus.

The communication interface is used for communication between the electronic equipment and other equipment.

The Memory may include a RAM (Random Access Memory) or an NVM (Non-Volatile Memory), such as at least one disk Memory. Alternatively, the memory may be at least one memory device located remotely from the processor.

The Processor may be a general-purpose Processor including a CPU (Central Processing Unit), an NP (Network Processor), and the like; but also a DSP (Digital Signal Processing), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component.

An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements any one of the speed deblurring methods.

In yet another embodiment provided herein, there is also provided a computer program product containing instructions that, when executed on a computer, cause the computer to perform any of the speed disambiguation methods described above.

In the above embodiments, the implementation may be wholly or partially realized 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 procedures or functions described in accordance with the embodiments of the application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, digital subscriber line) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.

It should be noted that, in this document, the technical features in the various alternatives can be combined to form the scheme as long as the technical features are not contradictory, and the scheme is within the scope of the disclosure of the present application. Relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The embodiments in the present specification are described in a related manner, each embodiment focuses on differences from other embodiments, and the same and similar parts in the embodiments are referred to each other.

The above description is only for the preferred embodiment of the present application and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application are included in the protection scope of the present application.

Claims

1. A method of velocity deblurring, the method comprising:

2. The method of claim 1, wherein obtaining multiple frames of radar signals and determining the power map of each frame of radar signals separately comprises:

acquiring analog-digital converter (ADC) data of each channel of the radar virtual antenna array to obtain multi-frame radar signals;

3. The method of claim 1, wherein the mapping each power map into a two-dimensional matrix in a range dimension and a doppler dimension to obtain a constant false alarm rate CFAR two-dimensional mask for each frame of radar signals comprises:

4. The method of claim 1, wherein the performing track correlation on the same object in the CFAR two-dimensional mask of each frame of radar signal according to the time sequence of each frame of radar signal to obtain the estimated motion speed and the estimated motion direction of each object respectively comprises:

5. The method of claim 1, wherein selecting the pre-processing MIMO compensation mode for each object from the pre-processing MIMO compensation modes according to the estimated motion velocity and the estimated motion direction of the object comprises:

6. A speed deblurring apparatus, comprising:

the power diagram acquisition unit is used for acquiring multi-frame radar signals and respectively determining the power diagram of each frame of radar signal;

7. The apparatus according to claim 6, wherein the power map obtaining unit is specifically configured to: acquiring analog-digital converter (ADC) data of each channel of the radar virtual antenna array to obtain multi-frame radar signals; performing two-dimensional fast Fourier transform on ADC data of each channel in each frame of radar signal to obtain a virtual array vector of each frame of radar signal; and respectively carrying out non-coherent accumulation on the virtual array vector of each frame of radar signal to obtain a power diagram of each frame of radar signal.

8. The apparatus of claim 6, wherein the CFAR detection unit is specifically configured to: aiming at each power map, carrying out CFAR detection on the power map to obtain a noise intensity threshold of the power map; and aiming at each power map, in a two-dimensional matrix of a distance dimension and a Doppler dimension, setting the power which is larger than the noise intensity threshold of the power map in the power map as a first value, and setting the power which is not larger than the noise intensity threshold of the power map in the power map as a second value to obtain a CFAR two-dimensional mask of the radar signal corresponding to the power map, wherein the area corresponding to the first value contains an object, and the area corresponding to the second value does not contain the object.

9. The apparatus according to claim 6, wherein the motion estimation unit is specifically configured to: performing connected domain analysis on each CFAR two-dimensional mask to obtain target information of each object in each CFAR two-dimensional mask, wherein the target information of the object comprises the object width, the object height and the object center coordinate of the object aiming at any object; according to the time sequence of each frame of radar signal and the target information of each object, carrying out track association on the same object in the CFAR two-dimensional mask of each frame of radar signal to respectively obtain the motion track of each object; and respectively determining the estimated motion speed and the estimated motion direction of each object at least according to the motion track of each object and the time difference between each frame of radar signal.

10. The apparatus according to claim 6, wherein the compensation pattern rejection unit is specifically configured to: aiming at each object, acquiring the motion direction and the motion speed of the object under each compensation mode in preset MIMO compensation modes; aiming at each object, selecting a compensation mode with the same motion direction as the estimated motion direction of the object from preset MIMO compensation modes to obtain a compensation mode after the object is filtered; and aiming at each object, selecting a compensation mode with the error between the motion speed and the estimated motion speed of the object within a preset range from the compensation modes after the object is filtered, so as to obtain a preprocessing MIMO compensation mode of the object.

11. An electronic device comprising a processor and a memory;

the memory is used for storing a computer program;

the processor, when executing the program stored in the memory, implementing the method of any of claims 1-5.

12. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 5.