阅读说明：本技术 一种基于雷达的目标对象三维点云生成方法及装置 (Target object three-dimensional point cloud generation method and device based on radar ) 是由 程毅 李彦龙 秦屹 王彬 刘志贤 陈红伟 成云丽 张晓飞 刘子华 于 2020-06-05 设计创作，主要内容包括：本申请公开了一种基于雷达的目标对象三维点云生成方法及装置,通过雷达发送啁啾信号,接收啁啾回波并进行采样和傅里叶变换获得第二数据矩阵,基于第二数据矩阵进行方位CAPON波束形成获得第三数据矩阵,通过恒虚警检测对第三数据矩阵中的数据进行计算确定各目标点；针对每个目标点,基于雷达最大观测方位角以及目标点坐标计算获得各目标点的方位角,对第二数据矩阵中与各目标点相对应的数据进行CAPON波束形成,计算获得各目标点的俯仰角,从而生成各目标点的三维点云。相对于传统方案,本申请提供的技术方案能够生成目标点的三维点云,从而有利于实现更精准的定位。(The application discloses a target object three-dimensional point cloud generating method and device based on a radar, wherein a chirp signal is sent by the radar, a chirp echo is received, sampling and Fourier transformation are carried out to obtain a second data matrix, azimuth CAPON beam forming is carried out based on the second data matrix to obtain a third data matrix, and data in the third data matrix are calculated through constant false alarm rate detection to determine each target point; and aiming at each target point, calculating to obtain the azimuth angle of each target point based on the maximum observation azimuth angle of the radar and the coordinates of the target point, performing CAPON beam forming on data corresponding to each target point in the second data matrix, and calculating to obtain the pitch angle of each target point so as to generate the three-dimensional point cloud of each target point. Compared with the traditional scheme, the technical scheme provided by the application can generate the three-dimensional point cloud of the target point, so that more accurate positioning can be realized.)

1. A target object three-dimensional point cloud generation method based on radar is characterized by comprising the following steps:

sequentially triggering Nt transmitting antennas of the radar to transmit chirp signals, wherein the transmitting antennas comprise azimuth transmitting antennas, and the heights of the azimuth transmitting antennas are consistent with that of a preset reference antenna;

performing ADC sampling processing on chirp echoes received by each receiving antenna of the radar to obtain a first data matrix with dimension Ns × Nc × Nra, where Nra is equal to Nt × Nr, Ns is the number of sampling points of the ADC sampling processing, Nc is the total number of chirp signals transmitted by the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp echoes;

performing fast Fourier transform on the data in the first data matrix to obtain a dimension N_{range_fft}Nc Nra, wherein N is the second data matrix_{range_fft}The number of fast Fourier transform points;

based on preset position dimension number N_aziAnd the second data matrix is used for forming an azimuth CAPON wave beam, and the obtained dimension is N_{range_fft}*N_aziThe azimuth transmit antenna, wherein the azimuth CAPON beamforming performs beamforming on data corresponding to the chirp signal transmitted by the azimuth transmit antenna in the second data matrix based on a CAPON algorithm;

performing constant false alarm detection based on the row data and the column data of the third data matrix respectively to obtain Nd target points;

aiming at each target point, calculating the azimuth angle of the corresponding target point based on the maximum observation azimuth angle of the radar and the coordinates of the corresponding target point, and obtaining the azimuth angle of each target point;

for each target point, performing CAPON beam forming based on data corresponding to the corresponding target point in the second data matrix, and calculating a pitch angle of the corresponding target point based on a preset pitch dimensional point number to obtain the pitch angle of each target point;

and generating the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively.

2. The radar-based target object three-dimensional point cloud generating method of claim 1, wherein said generating the three-dimensional point cloud of the target points based on the coordinates, azimuth angle, and pitch angle of the target points, respectively, comprises:

calculating the distance of each target point relative to the radar based on the coordinates of each target point respectively;

and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar respectively.

3. The radar-based target object three-dimensional point cloud generation method of claim 1, wherein the three-dimensional point cloud further comprises: velocity information of the corresponding target point;

after the pitch angles of the target points are obtained, the method further comprises the following steps:

respectively calculating the beam forming coefficients of all the target points;

for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point;

respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points;

aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point;

the generating of the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively is specifically as follows: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

4. The radar-based target object three-dimensional point cloud generating method of any one of claims 1 to 3, wherein the number of points based on a preset orientation dimension N is_aziAnd before the second data matrix is used for forming the azimuth CAPON beam, the method further comprises the following steps: performing fixed clutter suppression on the second data matrix;

based on preset position dimension number N_aziAnd the second data matrix performs azimuth CAPON beamforming specifically as follows:

based on preset position dimension number N_aziAnd performing azimuth CAPON beamforming on the second data matrix after the fixed clutter suppression.

5. A radar-based target object three-dimensional point cloud generating device is characterized by comprising:

the system comprises a signal sending module, a chirp signal sending module and a chirp signal sending module, wherein the signal sending module is used for sequentially triggering Nt transmitting antennas of a radar to transmit chirp signals, the transmitting antennas comprise azimuth transmitting antennas, and the heights of the azimuth transmitting antennas are consistent with a preset reference antenna;

an echo sampling module, configured to perform ADC sampling processing on chirp echoes received by respective receiving antennas of the radar, and obtain a first data matrix with a dimension Ns × Nc × Nra, where Nra × Nt Nr is the number of sampling points processed by the ADC sampling, Nc is the total number of chirp signals transmitted by the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp echoes;

a data processing module for performing fast Fourier transform on the data in the first data matrix to obtain a dimension N_{range_fft}Nc Nra, wherein N is the second data matrix_{range_fft}The number of fast Fourier transform points;

an azimuth beam forming module for forming an azimuth beam based on a preset number N of azimuth dimension points_aziAnd the second data matrix is used for forming an azimuth CAPON wave beam, and the obtained dimension is N_{range_fft}*N_aziThe azimuth transmit antenna, wherein the azimuth CAPON beamforming performs beamforming on data corresponding to the chirp signal transmitted by the azimuth transmit antenna in the second data matrix based on a CAPON algorithm;

the constant false alarm detection module is used for performing constant false alarm detection respectively based on the row data and the column data of the third data matrix to obtain Nd target points;

an azimuth calculation module, configured to calculate, for each target point, an azimuth of the corresponding target point based on the maximum observation azimuth of the radar and the coordinates of the corresponding target point, and obtain an azimuth of each target point;

a pitch angle calculation module, configured to perform CAPON beam forming on the basis of data corresponding to the corresponding target point in the second data matrix for each target point, and calculate a pitch angle of the corresponding target point on the basis of a preset number of pitch dimension points, so as to obtain a pitch angle of each target point;

and the three-dimensional point cloud generating module is used for generating the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively.

6. The target object three-dimensional point cloud generation apparatus of claim 5, wherein the three-dimensional point cloud generation module is specifically configured to:

calculating the distance of each target point relative to the radar based on the coordinates of each target point respectively;

and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar respectively.

7. The target object three-dimensional point cloud generating apparatus of claim 5, wherein the three-dimensional point cloud further comprises: velocity information of the corresponding target point;

the target object three-dimensional point cloud generating device further includes:

the speed calculation module is used for respectively calculating the beam forming coefficients of all the target points;

for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point;

respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points;

aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point;

the three-dimensional point cloud generating module is specifically configured to: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

8. The target object three-dimensional point cloud generating apparatus according to any one of claims 5 to 7, further comprising: the clutter suppression module is used for performing fixed clutter suppression on the second data matrix;

the azimuth beamforming module is specifically configured to:

based on preset position dimension number N_aziAnd performing azimuth CAPON beamforming on the second data matrix after the fixed clutter suppression.

9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 4 when executing the computer program.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 4.

Technical Field

The application relates to the field of radar detection, in particular to a target object three-dimensional point cloud generation method and device based on radar.

Background

With the development of the information era, the requirements of various industries on spatial data are increasing day by day, and the conventional data acquisition mode and data processing mode cannot meet the informatization requirements.

Disclosure of Invention

The application provides a target object three-dimensional point cloud generation method and device based on radar, which are beneficial to realizing more accurate positioning.

In order to achieve the above technical effect, a first aspect of the present application provides a target object three-dimensional point cloud generating method based on radar, including:

sequentially triggering Nt transmitting antennas of the radar to transmit chirp signals, wherein the transmitting antennas comprise azimuth transmitting antennas, and the heights of the azimuth transmitting antennas are consistent with that of a preset reference antenna;

performing ADC sampling processing on chirp echoes received by each receiving antenna of the radar to obtain a first data matrix with dimension Ns × Nc × Nra, where Nra is equal to Nt × Nr, Ns is the number of sampling points of the ADC sampling processing, Nc is the total number of chirp signals transmitted by the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp echoes;

performing fast Fourier transform on the data in the first data matrix to obtain a dimension N_{range_fft}Nc Nra, where N is the above_{range_fft}The number of fast Fourier transform points;

based on preset position dimension number N_aziAnd the second data matrix is used for forming an azimuth CAPON wave beam, and the obtained dimension is N_{range_fft}*N_aziThe third data matrix of (1), wherein the azimuth CAPON beamforming performs beamforming on data corresponding to the chirp signal transmitted by the azimuth transmitting antenna in the second data matrix based on a CAPON algorithm;

performing constant false alarm detection based on the row data and the column data of the third data matrix respectively to obtain Nd target points;

for each target point, calculating the azimuth angle of the corresponding target point based on the maximum observation azimuth angle of the radar and the coordinates of the corresponding target point, and obtaining the azimuth angle of each target point;

for each target point, performing CAPON beam forming based on data corresponding to the corresponding target point in the second data matrix, and calculating a pitch angle of the corresponding target point based on a preset pitch dimensional point number to obtain the pitch angle of each target point;

and generating three-dimensional point cloud of each target point based on the coordinates, azimuth angles and pitch angles of the target points respectively.

Optionally, the generating the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle, and the pitch angle of each target point respectively includes:

calculating the distance between each target point and the radar based on the coordinates of each target point;

and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar.

Optionally, the three-dimensional point cloud further includes: velocity information of the corresponding target point;

after the pitch angles of the target points are obtained, the method further comprises the following steps:

respectively calculating the beam forming coefficients of the target points;

for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point;

respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points;

aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point;

the generating of the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively is specifically as follows: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

Optionally, the number N of the orientation dimension points based on the presetting_aziAnd before the second data matrix performs the azimuth CAPON beamforming, the method further comprises: performing fixed clutter suppression on the second data matrix;

the number of the orientation dimension points N based on the presetting_aziAnd the second data matrix performing azimuth CAPON beamforming specifically comprises:

based on preset position dimension number N_aziAnd performing azimuth CAPON beamforming on the second data matrix after the fixed clutter suppression.

A second aspect of the present application provides a radar-based target object three-dimensional point cloud generating apparatus, including:

the system comprises a signal sending module, a receiving module and a sending module, wherein the signal sending module is used for sequentially triggering Nt transmitting antennas of a radar to transmit chirp signals, the transmitting antennas comprise azimuth transmitting antennas, and the heights of the azimuth transmitting antennas are consistent with a preset reference antenna;

an echo sampling module, configured to perform ADC sampling processing on chirp echoes received by each receiving antenna of the radar to obtain a first data matrix with dimension Ns × Nc × Nra, where Nra equals Nt Nr, Ns is the number of sampling points in the ADC sampling processing, Nc is the total number of chirp signals transmitted by the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp echoes;

a data processing module for performing fast Fourier transform on the data in the first data matrix to obtain dimension N_{range_fft}Nc Nra, where N is the above_{range_fft}The number of fast Fourier transform points;

an azimuth beam forming module for forming an azimuth beam based on a preset number N of azimuth dimension points_aziAnd the second data matrix is used for forming an azimuth CAPON wave beam, and the obtained dimension is N_{range_fft}*N_aziThe third data matrix of (1), wherein the azimuth CAPON beamforming performs beamforming on data corresponding to the chirp signal transmitted by the azimuth transmitting antenna in the second data matrix based on a CAPON algorithm;

the constant false alarm detection module is used for performing constant false alarm detection respectively based on the row data and the column data of the third data matrix to obtain Nd target points;

an azimuth calculation module, configured to calculate, for each target point, an azimuth of the corresponding target point based on the maximum observation azimuth of the radar and the coordinates of the corresponding target point, and obtain an azimuth of each target point;

a pitch angle calculation module, configured to perform CAPON beam forming on each target point based on data corresponding to the corresponding target point in the second data matrix, and calculate a pitch angle of the corresponding target point based on a preset number of pitch dimension points to obtain a pitch angle of each target point;

and the three-dimensional point cloud generating module is used for generating the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively.

Optionally, the three-dimensional point cloud generating module is specifically configured to:

calculating the distance between each target point and the radar based on the coordinates of each target point;

and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar.

Optionally, the three-dimensional point cloud further includes: velocity information of the corresponding target point;

the radar-based target object three-dimensional point cloud generating device further comprises:

a velocity calculation module for calculating the beam forming coefficients of the target points respectively;

for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point;

respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points;

aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point;

the three-dimensional point cloud generating module is specifically configured to: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

Optionally, the apparatus for generating a three-dimensional point cloud of a target object further includes: the clutter suppression module is used for performing fixed clutter suppression on the second data matrix;

the azimuth beam forming module is specifically configured to:

based on preset position dimension number N_aziAnd the second data moment after fixed clutter suppressionThe array performs azimuth CAPON beamforming.

A third aspect of the present application provides a computer device, comprising a memory and a processor, wherein the memory stores a software program, and the processor implements the steps of the radar-based target object three-dimensional point cloud generating method when executing the software program.

A fourth aspect of the present application provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described radar-based target object three-dimensional point cloud generation method.

According to the method, a chirp signal is sent through a radar, chirp echoes are received, sampling and Fourier transformation are carried out to obtain a second data matrix, azimuth CAPON beam forming is carried out based on the second data matrix to obtain a third data matrix, and data in the third data matrix are calculated through constant false alarm rate detection to determine each target point; and aiming at each target point, calculating to obtain the azimuth angle of each target point based on the maximum observation azimuth angle of the radar and the coordinates of the target point, performing CAPON beam forming on data corresponding to each target point in the second data matrix, and calculating to obtain the pitch angle of each target point so as to generate the three-dimensional point cloud of each target point. According to the scheme, each target point is determined through constant false alarm detection, the azimuth angle of each target point is obtained through calculation based on the maximum observation azimuth angle of the radar and the coordinates of the target point, CAPON beam forming is carried out on data corresponding to each target point in the second data matrix, the pitch angle of each target point is obtained through calculation, therefore, the three-dimensional point cloud of the target point can be generated based on the pitch angle, the azimuth angle and the coordinates of the target point, the three-dimensional point cloud of the target point can provide information of more dimensions of the target point, and more accurate positioning is facilitated.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.

Fig. 1 is a flowchart of a method for generating a target object three-dimensional point cloud based on radar according to an embodiment of the present disclosure;

fig. 2 is a schematic diagram of a transmitting antenna provided in an embodiment of the present application;

fig. 3 is a schematic diagram of a target object three-dimensional point cloud generating device based on radar according to an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It is also to be understood that the terminology used in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when …" or "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted depending on the context to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "[ in response to detecting [ described condition or event ]".

The technical solutions in the embodiments of the present application are clearly and completely described below with reference to the drawings of 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.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways than those described herein, and it will be apparent to those of ordinary skill in the art that the present application is not limited by the specific embodiments disclosed below.

A first aspect of the embodiments of the present application provides a target object three-dimensional point cloud generating method based on a radar, and fig. 1 shows a specific process of the target object three-dimensional point cloud generating method based on a radar provided in the embodiments of the present application, and details are described as follows with reference to fig. 1:

step 101, sequentially triggering Nt transmitting antennas of a radar to transmit chirp signals;

the transmitting antenna comprises an azimuth transmitting antenna, and the height of the azimuth transmitting antenna is consistent with that of a preset reference antenna.

Fig. 2 shows a schematic diagram of a transmitting antenna provided in an embodiment of the present application, and as shown in fig. 2, the transmitting antenna includes an azimuth transmitting antenna 201 and a tilt transmitting antenna 202, where an antenna having the same height as a preset reference antenna 201 is the azimuth transmitting antenna 201 (the reference antenna itself also serves as an azimuth transmitting antenna), and an antenna having a different height from the preset reference antenna 201 is the tilt transmitting antenna 202. The Nt transmitting antennas include Nta azimuth transmitting antennas 201 and Ntb elevation transmitting antennas 202, where Ntb is Nt-Nta; the number of the azimuth transmitting antenna 201 is 1, 2, and Nta, and the number of the elevation transmitting antenna 202 is Nta +1, Nta +2, and Nt.

In this embodiment, the azimuth transmitting antenna 201 and the elevation transmitting antenna 202 are sequentially triggered according to the numbers, and the azimuth transmitting antenna 201 and the elevation transmitting antenna 202 sequentially transmit a single chirp signal.

102, performing ADC (analog to digital converter) sampling processing on chirp echoes received by each receiving antenna of the radar to obtain a first data matrix;

the dimension of the first data matrix is Ns × Nc × Nra.

Where Nra is Nt Nr, Ns is the number of sampling points of the ADC sampling process, Nc is the total number of chirp signals transmitted from the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp.

In this embodiment, when each of the transmitting antennas transmits a chirp signal, all of the Nr receiving antennas simultaneously receive chirp echoes, and perform ADC sampling on the chirp echoes, where the number of sampling points of each chirp echo is Ns. When a first transmitting antenna (namely a transmitting antenna with the number of 1) is used for transmitting, the chirp echo numbers received by Nr receiving antennas are marked as 1, 2, ·, Nr; when the second transmitting antenna (i.e. the transmitting antenna numbered 2) transmits, the chirp echo numbers received by the Nr receiving antennas are recorded as Nr +1, Nr +2, ·, 2 Nr; and so on. When the n transmitting antennas sequentially transmit chirp signals, a total equivalent of n × Nr equivalent receiving antennas receives the chirp signals, and the number of the equivalent receiving antennas is defined as Nra, where Nra is equal to Nt × Nr. Meanwhile, when the azimuth transmitting antenna 201 transmits a chirp signal, the equivalent receiving antenna that receives a chirp echo is an equivalent azimuth receiving antenna, and when the pitch transmitting antenna 202 transmits a chirp signal, the equivalent receiving antenna that receives a chirp echo is an equivalent pitch receiving antenna. The number of the equivalent azimuth receiving antennas is Na ═ Nta × (Nr). And arranging chirp echoes and carrying out ADC (analog-to-digital converter) sampling according to the chirp echo number received by the receiving antenna, and obtaining a first data matrix with dimension Ns Nc Nra after the transmitting antenna transmits Nc chirp signals.

Alternatively, the number and arrangement of the chirp echoes may be in other manners, and are not limited in detail herein.

103, performing fast fourier transform on the data in the first data matrix to obtain a second data matrix;

wherein the dimension of the second data matrix is N_{range_fft}*Nc*Nra。

Wherein, the above-mentioned N_{range_fft}The number of fast fourier transform points. In this embodiment, the second data matrix is denoted as X_ncrWherein N is 1, 2, N_{range_fft}N is defined as the second data matrix X, c is 1, 2, Nc, r is 1, 2, Nra_ncrDefining r as the second data matrix X_ncrThe second dimension index of (2).

104, forming a position CAPON wave beam based on a preset position dimension point and the second data matrix to obtain a third data matrix;

wherein the number of the preset orientation dimension points is N_aziThe dimension of the third data matrix is N_{range_fft}*N_azi。

Wherein the azimuth CAPON beamforming is based on a CAPON algorithm for the second data matrix X_ncrAnd performing beam forming on the data corresponding to the chirp signal transmitted by the azimuth transmitting antenna.

Optionally, the second data matrix X is used_ncrThe data in (1) is numbered, and the number of the second dimensional index r of the data corresponding to the chirp echoes received by the Na equivalent azimuth receiving antennas is set to 1, 2, ·, Na. Calculating the second data matrix X by the first formula_ncrThe covariance matrix corresponding to the data received by the equivalent azimuth receiving antenna, wherein the first formula is:

wherein R is_nFor the second data matrix X_ncrThe covariance matrix corresponding to the data received by the equivalent azimuth receiving antenna, r 1, 2, Na, N1, 2_{range_fft}。

Calculating the phase difference mu of the chirp echoes received between two adjacent receiving antennas through a second formula_aWherein the second formula is:

wherein a is 1, 2, N_azi，N_aziThe number of the azimuth dimension points is preset and is related to the azimuth angle of the radar, and when the azimuth angle of the radar is [ -theta [ ]_max，θ_max]When N is present_azi＝2·θ_max+1，θ_maxIs the maximum observed azimuth of the radar; a is an azimuth index corresponding to each azimuth dimension point, and particularly, the azimuth angle of the radar is divided into N_aziA point of azimuth dimension, a being N_aziThe azimuth indexes corresponding to the azimuth dimension points; theta_aFor azimuth angle, theta, corresponding to the a-th azimuthal dimension_a＝-θ_max+ a-1; d is the distance between the receiving antennas which are arranged equidistantly; λ is the wavelength of the electromagnetic wave emitted by the radar.

Calculating the azimuth angle theta of the Na equivalent azimuth receiving antennas through a third formula_aDirectional vector α_aWherein the third formula is:

calculating and obtaining the echo amplitude P of each data point by a fourth formula_naWherein the fourth formula is:

wherein N is 1, 2, N_{range_fft}；a＝1，2，···，N_aziAll of the above P_naComposition dimension of N_{range_fft}*N_aziThe third data matrix P.

Optionally, the number N of the orientation dimension points based on the presetting_aziAnd before the second data matrix performs the azimuth CAPON beamforming, the method further comprises: for the second data matrix X_ncrPerforming fixed clutter suppression; the number of the orientation dimension points N based on the presetting_aziAnd the second data matrix X_ncrThe specific steps for forming the azimuth CAPON beam are as follows: based on preset position dimension number N_aziAnd a second data matrix X after stationary clutter suppression_ncrAnd performing azimuth CAPON beamforming.

In this embodiment, the fixed clutter suppression is performed by a calculation method shown in a fifth formula, where the fifth formula is:

wherein N is 1, 2, N_{range_fft}，r＝1，2，···，Nra。

And 105, performing constant false alarm detection respectively based on the row data and the column data of the third data matrix to obtain Nd target points.

In an application scenario, let N be 1, 2, N_{range_fft}Performing constant false alarm detection based on the column data of each column of the third data matrix P to obtain a column target point on each column, wherein the coordinate of the kth column target point is (r)_k,a_k) (ii) a For the k column target point, respectively carrying out constant false alarm detection on the corresponding row data in the third data matrix P to obtain a row target point, and if the row target point is obtainedDetermining a target point detected by the constant false alarm at the k-th point, namely a point where the target object is located, if the abscissa is the same as the abscissa of the column of target points; calculating the coordinates of the row target points of all the column target points, comparing the coordinates to finally obtain Nd target points (r)_m,a_m) Wherein m is 1, 2, Nd.

In another application scenario, the constant false alarm detection may be performed on the row data of each row of the third data matrix P to obtain row target points on each row, and then the column data corresponding to the row target points is calculated to obtain column target points, which are finally compared to obtain target points for constant false alarm detection, which is not limited herein.

And 106, aiming at each target point, calculating the azimuth angle of the corresponding target point based on the maximum observation azimuth angle of the radar and the coordinates of the corresponding target point, and obtaining the azimuth angle of each target point.

Specifically, the mth target point (r) is calculated by the sixth formula_m,a_m) Azimuth angle theta of_mWherein the sixth formula is:

θ_m＝-θ_max+a_m-1

wherein m is 1, 2, Nd, theta_mIs the azimuth angle, θ, of the m-th target point_maxThe maximum azimuth angle of observation of the radar.

And 107, performing CAPON beam forming on each target point based on the data corresponding to the corresponding target point in the second data matrix, and calculating the pitch angle of the corresponding target point based on the preset pitch dimensionality number to obtain the pitch angle of each target point.

Optionally, based on the number N of preset pitching dimension points_eleCalculating the phase difference mu of the received signals between two adjacent equivalent azimuth receiving antennas by a seventh formula_m,iAnd the phase difference upsilon of the receiving signals between two adjacent equivalent pitch receiving antennas_iWherein, the seventh formula is:

wherein i is 1, 2, N_eleNumber of pitch dimension N_eleThe view angle in the elevation direction of the radar is set toWhen the temperature of the water is higher than the set temperature,

wherein the content of the first and second substances,the maximum observation pitch angle of the radar; each pitching dimensional point corresponds to a pitching dimensional index, and the pitching dimensional index is recorded as i;for the pitch angle corresponding to the ith pitch dimension,

respectively calculating the pitch angles of the Nra equivalent receiving antennas corresponding to each constant false alarm detection point

Directional vector in the direction in which Nra equivalent receiving antennas corresponding to the mth target point are in pitch

Directional vector α_m,iIs calculated as shown in the eighth formula:

wherein the content of the first and second substances,

and calculating and obtaining a pitch power spectrum corresponding to the mth target point through a ninth formula, wherein the ninth formula is as follows:

wherein, P_m,iIs 1 × N_eleThe vector of (c) corresponds to the pitch power spectrum of the mth target point.

Obtaining the pitch power spectrum P of the mth target point_m,iPitch dimension index imax corresponding to medium amplitude maximum point_mObtaining the pitch angle of the mth target point by the tenth formula

And 108, generating a three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively.

Optionally, the generating the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle, and the pitch angle of each target point respectively includes: calculating the distance between each target point and the radar based on the coordinates of each target point; and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar.

In this embodiment, for the mth target point, the constant false alarm detection coordinate is (r)_m,a_m) (ii) a Detecting coordinates (r) according to its constant false alarm_m,a_m) And calculating and obtaining the distance of the mth target point relative to the radar by an eleventh formula, wherein the eleventh formula is as follows:

range_m＝(r_m-1)·dr

and calculating and obtaining the three-dimensional coordinate of the mth target point relative to the radar through a twelfth formula, wherein the twelfth formula is as follows:

producing three-dimensional point cloud information (x) of the mth target point based on the three-dimensional coordinates of the mth target point relative to the radar_m,y_m,z_m) And output.

Optionally, the three-dimensional point cloud further includes: velocity information of the corresponding target point; after the pitch angles of the target points are obtained, the method further comprises the following steps: respectively calculating the beam forming coefficients of the target points; for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point; respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points; aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point; the generating of the three-dimensional point cloud of each target point based on the coordinates, the azimuth angle and the pitch angle of each target point respectively is specifically as follows: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

In this embodiment, for the mth target point, the above Nra equivalent receiving antennas at the azimuth angle θ are obtained by the thirteenth formula_mAnd a pitch angleUpper guide vector α_mWherein, the thirteenth formula is:

wherein the content of the first and second substances,

and obtaining a beam forming coefficient corresponding to the mth target point through a fourteenth formula, where the fourteenth formula is:

wherein the beam forming coefficient w of the mth target point_mIs a vector of Nra × 1.

For the mth object point, based on the beam forming coefficient w_mFor the second data matrix X_ncrPerforming beam forming on the data corresponding to the mth target point, and calculating a beam vector corresponding to the mth point according to a fifteenth formula, wherein the fifteenth formula is as follows:

X_bf＝X_kcr×w_m

wherein r is 1, 2, Nra; c 1, 2, ·, Nc; k is r_mDetecting the abscissa for the constant false alarm of the mth target point; x_bfIs an Nc × 1 dimensional vector.

For the m-th object point, for the beam vector X_bfPerforming fast Fourier transform to obtain the Doppler spectrum corresponding to the mth target point, and obtaining the point where the maximum amplitude value in the Doppler spectrum corresponding to the mth target point is located, and recording the point as the maximum amplitude value point d corresponding to the mth target point_mAnd calculates the velocity of the above-mentioned mth target point by a sixteenth formula, wherein,the sixteenth formula is:

velocity_m＝(d_m-1)·dv

based on the coordinates (r) of the m-th target point_m,a_m) Azimuth angle theta_mAnd a pitch angleAnd speed d_mAnd generating the three-dimensional point cloud of the mth target point. Specifically, the three-dimensional coordinates of the mth target point relative to the radar are calculated by the twelfth formula, and the velocity d of the mth target point is combined_mObtaining a three-dimensional point cloud [ velocity ] of the mth target point containing the speed and the three-dimensional coordinates of the target point_m,x_m,y_m,z_m]。

Optionally, the distance range of the mth point may be further determined_mAzimuth angle theta_mAnd a pitch angle

Adding the three-dimensional point cloud to obtain a three-dimensional point cloud containing the distance, azimuth angle, pitch angle, speed and three-dimensional coordinate of the mth target point

The above calculation process takes the mth target point as an example, and actually all Nd target points need to be calculated. Optionally, all Nd target points may be directly and simultaneously calculated, or m ═ 1, 2, ·, Nd may be sequentially and cyclically calculated until all Nd target points are calculated.

Optionally, the radar is a millimeter wave radar, and in this embodiment, the radar is a 60GHz mimo millimeter wave radar.

As can be seen from the above, in the method for generating a target object three-dimensional point cloud based on a radar, a chirp signal is sent by the radar, a chirp echo is received, sampling and fourier transform are performed to obtain a second data matrix, azimuth CAPON beam forming is performed based on the second data matrix to obtain a third data matrix, and data in the third data matrix is calculated through constant false alarm detection to determine each target point; and aiming at each target point, calculating to obtain the azimuth angle of each target point based on the maximum observation azimuth angle of the radar and the coordinates of the target point, performing CAPON beam forming on data corresponding to each target point in the second data matrix, and calculating to obtain the pitch angle of each target point so as to generate the three-dimensional point cloud of each target point. According to the scheme, each target point is determined through constant false alarm detection, the azimuth angle of each target point is obtained through calculation based on the maximum observation azimuth angle of the radar and the coordinates of the target point, CAPON beam forming is carried out on data corresponding to each target point in the second data matrix, the pitch angle of each target point is obtained through calculation, therefore, the three-dimensional point cloud of the target point can be generated based on the pitch angle, the azimuth angle and the coordinates of the target point, the three-dimensional point cloud of the target point can provide information of more dimensions of the target point, and more accurate positioning is facilitated.

Corresponding to the target object three-dimensional point cloud generating method based on radar, the embodiment of the present application further provides a target object three-dimensional point cloud generating device based on radar, as shown in fig. 3, where the target object three-dimensional point cloud generating device based on radar includes:

the signal sending module 301 is configured to sequentially trigger Nt transmitting antennas of the radar to transmit chirp signals, where the transmitting antennas include azimuth transmitting antennas, and heights of the azimuth transmitting antennas are consistent with a preset reference antenna.

Optionally, the transmitting antenna includes an azimuth transmitting antenna and a pitching transmitting antenna, where an antenna having the same height as the preset reference antenna is the azimuth transmitting antenna (the reference antenna itself is also used as an azimuth transmitting antenna), and an antenna having a different height from the preset reference antenna is the pitching transmitting antenna. The Nt transmitting antennas comprise Nta azimuth transmitting antennas and Ntb elevation transmitting antennas, wherein Ntb is Nt-Nta; and the numbers of the azimuth transmitting antenna are 1, 2, and Nta, and the numbers of the elevation transmitting antenna are Nta +1, Nta +2, and Nt.

In the embodiment of the present application, the azimuth transmitting antenna and the elevation transmitting antenna are sequentially triggered according to the number, and the azimuth transmitting antenna and the elevation transmitting antenna sequentially transmit a single chirp signal.

The echo sampling module 302 performs ADC sampling processing on chirp echoes received by each receiving antenna of the radar to obtain a first data matrix with dimension Ns × Nc × Nra.

Where Nra is Nt Nr, Ns is the number of sampling points of the ADC sampling process, Nc is the total number of chirp signals transmitted from the Nt transmitting antennas, and Nr is the total number of receiving antennas used by the radar to receive the chirp.

In this embodiment, when each of the transmitting antennas transmits a chirp signal, all of the Nr receiving antennas simultaneously receive chirp echoes, and perform ADC sampling on the chirp echoes, where the number of sampling points of each chirp echo is Ns. When a first transmitting antenna (namely a transmitting antenna with the number of 1) is used for transmitting, the chirp echo numbers received by Nr receiving antennas are marked as 1, 2, ·, Nr; when the second transmitting antenna (i.e. the transmitting antenna numbered 2) transmits, the chirp echo numbers received by the Nr receiving antennas are recorded as Nr +1, Nr +2, ·, 2 Nr; and so on. When the n transmitting antennas sequentially transmit chirp signals, a total equivalent of n × Nr equivalent receiving antennas receives the chirp signals, and the number of the equivalent receiving antennas is defined as Nra, where Nra is equal to Nt × Nr. Meanwhile, when the azimuth transmitting antenna transmits the chirp signal, the equivalent receiving antenna for receiving the chirp echo is the equivalent azimuth receiving antenna, and when the elevation transmitting antenna transmits the chirp signal, the equivalent receiving antenna for receiving the chirp echo is the equivalent elevation receiving antenna. The number of the equivalent azimuth receiving antennas is Na ═ Nta × (Nr). And arranging chirp echoes and carrying out ADC (analog-to-digital converter) sampling according to the chirp echo number received by the receiving antenna, and obtaining a first data matrix with dimension Ns Nc Nra after the transmitting antenna transmits Nc chirp signals.

Alternatively, the number and arrangement of the chirp echoes may be in other manners, and are not limited in detail herein.

A data processing module 303, configured to perform fast fourier transform on the data in the first data matrix to obtain a dimensionIs N_{range_fft}Nc Nra.

Wherein, the above-mentioned N_{range_fft}The number of fast fourier transform points. In this embodiment, the second data matrix is denoted as X_ncrWherein N is 1, 2, N_{range_fft}N is defined as the second data matrix X, c is 1, 2, Nc, r is 1, 2, Nra_ncrDefining r as the second data matrix X_ncrThe second dimension index of (2).

An azimuth beam forming module 304 for forming an azimuth beam based on the number N of preset azimuth dimension points_aziAnd the second data matrix is used for forming an azimuth CAPON wave beam, and the obtained dimension is N_{range_fft}*N_aziThe third data matrix of (1).

Wherein the azimuth CAPON beamforming is based on a CAPON algorithm for the second data matrix X_ncrAnd performing beam forming on the data corresponding to the chirp signal transmitted by the azimuth transmitting antenna.

Optionally, the second data matrix X is used_ncrThe data in (1) is numbered, and the number of the second dimensional index r of the data corresponding to the chirp echoes received by the Na equivalent azimuth receiving antennas is set to 1, 2, ·, Na. Calculating the second data matrix X by the seventeenth formula_ncrThe covariance matrix corresponding to the data received by the equivalent azimuth receiving antenna, wherein the seventeenth formula is:

wherein R is_nFor the second data matrix X_ncrThe covariance matrix corresponding to the data received by the equivalent azimuth receiving antenna, r 1, 2, Na, N1, 2_{range_fft}。

Calculating the phase difference mu of the chirp echo received between two adjacent receiving antennas by using an eighteenth formula_aWherein, the eighteenth formula is:

wherein a is 1, 2. N_azi，N_aziThe number of the azimuth dimension points is preset and is related to the azimuth angle of the radar, and when the azimuth angle of the radar is [ -theta [ ]_max，θ_max]When N is present_azi＝2·θ_max+1，θ_maxIs the maximum observed azimuth of the radar; a is an azimuth index corresponding to each azimuth dimension point, and particularly, the azimuth angle of the radar is divided into N_aziA point of azimuth dimension, a being N_aziThe azimuth indexes corresponding to the azimuth dimension points; theta_aFor azimuth angle, theta, corresponding to the a-th azimuthal dimension_a＝-θ_max+ a-1; d is the distance between the receiving antennas which are arranged equidistantly; λ is the wavelength of the electromagnetic wave emitted by the radar.

Calculating the azimuth angle theta of the Na equivalent azimuth receiving antennas through a nineteenth formula_aDirectional vector α_aWherein the nineteenth formula is:

calculating and obtaining the echo amplitude P of each data point by a twentieth formula_naWherein the twentieth formula is:

wherein N is 1, 2, N_{range_fft}；a＝1，2，···，N_aziAll of the above P_naComposition dimension of N_{range_fft}*N_aziThe third data matrix P.

Optionally, the apparatus for generating a three-dimensional point cloud of a target object further includes: a clutter suppression module (not shown) for suppressing the second data matrix X_ncrPerforming fixed clutter suppression; the azimuth beam forming module is specifically configured to: based on preset position dimension number N_aziAndsecond data matrix X after stationary clutter suppression_ncrAnd performing azimuth CAPON beamforming.

In this embodiment, the fixed clutter suppression is performed by a calculation method shown by a twenty-first formula, where the twenty-first formula is:

wherein N is 1, 2, N_{range_fft}，r＝1，2，···，Nra。

And a constant false alarm detection module 305, configured to perform constant false alarm detection based on the row data and the column data of the third data matrix P, respectively, to obtain Nd target points.

In an application scenario, let N be 1, 2, N_{range_fft}Performing constant false alarm detection based on the column data of each column of the third data matrix P to obtain a column target point on each column, wherein the coordinate of the kth column target point is (r)_k,a_k) (ii) a For the kth column target point, respectively performing constant false alarm detection on corresponding row data in the third data matrix P to obtain a row target point, and if the abscissa of the obtained row target point is the same as the abscissa of the column target point, determining the target point of the constant false alarm detection of the kth point, namely the point where the target object is located; calculating the coordinates of the row target points of all the column target points, comparing the coordinates to finally obtain Nd target points (r)_m,a_m) Wherein m is 1, 2, Nd.

In another application scenario, the constant false alarm detection may be performed on the row data of each row of the third data matrix P to obtain row target points on each row, and then the column data corresponding to the row target points is calculated to obtain column target points, which are finally compared to obtain target points for constant false alarm detection, which is not limited herein.

An azimuth calculation module 306 for calculating, for each target point, an azimuth of the corresponding target point based on the maximum observed azimuth of the radar and the coordinates of the corresponding target point, obtaining an azimuth of each target point,

specifically, the mth target point (r) is calculated by the twenty-second formula_m,a_m) Azimuth angle theta of_mWherein the twenty-second formula is:

θ_m＝-θ_max+a_m-1

wherein m is 1, 2, Nd, theta_mIs the azimuth angle, θ, of the m-th target point_maxThe maximum azimuth angle of observation of the radar.

And a pitch angle calculation module 307, configured to perform CAPON beam forming on each target point based on data corresponding to the corresponding target point in the second data matrix, and calculate a pitch angle of the corresponding target point based on a preset number of pitch dimension points, so as to obtain a pitch angle of each target point.

Optionally, based on the number N of preset pitching dimension points_eleCalculating the phase difference mu of the received signals between two adjacent equivalent azimuth receiving antennas by the twenty-third formula_m,iAnd the phase difference upsilon of the receiving signals between two adjacent equivalent pitch receiving antennas_iWherein the twenty-third formula is:

wherein i is 1, 2, N_eleNumber of pitch dimension N_eleThe view angle in the elevation direction of the radar is set to

When the temperature of the water is higher than the set temperature,wherein the content of the first and second substances,

the maximum observation pitch angle of the radar; each pitching dimensional point corresponds to a pitching dimensional index, and the pitching dimensional index is recorded as i;for the pitch angle corresponding to the ith pitch dimension,

respectively calculating the pitch angles of the Nra equivalent receiving antennas corresponding to each constant false alarm detection point

Directional vector in the direction in which Nra equivalent receiving antennas corresponding to the mth target point are in pitchDirectional vector α_m,iIs calculated as shown in the twenty-fourth formula:

wherein the content of the first and second substances,

and calculating and obtaining a pitch power spectrum corresponding to the mth target point through a twenty-fifth formula, wherein the twenty-fifth formula is as follows:

wherein, P_m,iIs 1 × N_eleThe vector of (c) corresponds to the pitch power spectrum of the mth target point.

Obtaining the pitch power spectrum P of the mth target point_m,iPitch dimension index imax corresponding to medium amplitude maximum point_mObtaining the pitch angle of the mth target point through a twenty-sixth formula

Wherein the twenty-sixth formula is:

and a three-dimensional point cloud generating module 308, configured to generate a three-dimensional point cloud of each target point based on the coordinates, the azimuth angle, and the pitch angle of each target point.

Optionally, the three-dimensional point cloud generating module 308 is specifically configured to: calculating the distance between each target point and the radar based on the coordinates of each target point; and generating a three-dimensional point cloud of each target point relative to the radar based on the azimuth angle and the pitch angle of each target point and the distance between each target point and the radar.

In this embodiment, for the mth target point, the constant false alarm detection coordinate is (r)_m,a_m) (ii) a Detecting coordinates (r) according to its constant false alarm_m,a_m) And calculating and obtaining the distance of the mth target point relative to the radar through a twenty-seventh formula, wherein the twenty-seventh formula is as follows:

range_m＝(r_m-1)·dr

and calculating and obtaining the three-dimensional coordinate of the mth target point relative to the radar through a twenty-eighth formula, wherein the twenty-eighth formula is as follows:

producing three-dimensional point cloud information (x) of the mth target point based on the three-dimensional coordinates of the mth target point relative to the radar_m,y_m,z_m) And output.

Optionally, the three-dimensional point cloud further includes: velocity information of the corresponding target point; the radar-based target object three-dimensional point cloud generating device further comprises:

a velocity calculating module (not shown in the figure) for calculating the beam forming coefficients of the target points respectively; for each target point, performing beam forming on data corresponding to the corresponding target point in the second data matrix based on a beam forming coefficient of the corresponding target point to obtain a beam vector corresponding to the corresponding target point; respectively carrying out fast Fourier transform on the beam vectors of all target points to obtain Doppler spectrums corresponding to all the target points; aiming at each target point, calculating the speed of the corresponding target point based on the maximum amplitude point in the Doppler spectrum corresponding to the corresponding target point; the three-dimensional point cloud generating module 308 is specifically configured to: and generating the three-dimensional point cloud of each target point based on the coordinates, azimuth angles, pitch angles and speeds of the target points respectively.

In this embodiment, for the mth target point, the Nra equivalent receiving antennas are calculated and obtained by the twenty-ninth formula at the azimuth angle θ_mAnd a pitch angle

Upper guide vector α_mWherein the twenty-ninth formula is:

wherein the content of the first and second substances,

and calculating and obtaining a beam forming coefficient corresponding to the mth target point through a thirty formula, wherein the thirty formula is as follows:

wherein the beam forming coefficient w of the mth target point_mIs a vector of Nra × 1.

For the mth object point, based on the beam forming coefficient w_mFor the second data matrix X_ncrPerforming beam forming on the data corresponding to the mth target point, and calculating a beam vector corresponding to the mth point by using a thirty-first formula, where the thirty-first formula is:

X_bf＝X_kcr×w_m

wherein r is 1, 2, Nra; c 1, 2, ·, Nc; k is r_mWherein r is_mDetecting the abscissa for the constant false alarm of the mth target point; x_bfIs an Nc × 1 dimensional vector.

For the m-th object point, for the beam vector X_bfPerforming fast Fourier transform to obtain the Doppler spectrum corresponding to the mth target point, and obtaining the point where the maximum amplitude value in the Doppler spectrum corresponding to the mth target point is located, and recording the point as the maximum amplitude value point d corresponding to the mth target point_mAnd calculating the velocity of the mth target point by a thirty-second formula, wherein the thirty-second formula is as follows:

velocity_m＝(d_m-1)·dv

based on the coordinates (r) of the m-th target point_m,a_m) Azimuth angle theta_mAnd a pitch angleAnd speed d_mAnd generating the three-dimensional point cloud of the mth target point. Specifically, the three-dimensional of the mth target point relative to the radar is calculated by the above-mentioned twenty-eighth formulaCoordinates in combination with the velocity d of the m-th target point_mObtaining a three-dimensional point cloud [ velocity ] of the mth target point containing the speed and the three-dimensional coordinates of the target point_m,x_m,y_m,z_m]。

Optionally, the distance range of the mth point may be further determined_mAzimuth angle theta_mAnd a pitch angleAdding the three-dimensional point cloud to obtain a three-dimensional point cloud containing the distance, azimuth angle, pitch angle, speed and three-dimensional coordinate of the mth target point

The above calculation process takes the mth target point as an example, and actually all Nd target points need to be calculated. Optionally, all Nd target points may be directly and simultaneously calculated, or m ═ 1, 2, ·, Nd may be sequentially and cyclically calculated until all Nd target points are calculated.

Optionally, the radar is a millimeter wave radar, and in this embodiment, the radar is a 60GHz mimo millimeter wave radar.

As can be seen from the above, in the target object three-dimensional point cloud generating device based on radar provided in the embodiment of the present application, the signal sending module 301 triggers the radar to send a chirp signal, the echo sampling module 302 receives a chirp echo and performs sampling to obtain a first data matrix, the data processing module 303 performs fourier transform to obtain a second data matrix, the azimuth beam forming module 304 performs azimuth CAPON beam forming based on the second data matrix to obtain a third data matrix, and the constant false alarm detection module 305 calculates data in the third data matrix to determine each target point; for each target point, the azimuth angle of each target point is calculated and obtained by the azimuth angle calculation module 306, and the pitch angle of each target point is calculated and obtained by the pitch angle calculation module 307, so that the three-dimensional point cloud of each target point is generated by the three-dimensional point cloud generation module 308. According to the scheme, each target point is determined by the constant false alarm detection module 305, and the pitch angle and the azimuth angle of the determined target point are calculated by the azimuth angle calculation module 306 and the pitch angle calculation module 307 respectively, so that the three-dimensional point cloud of the target point is generated by the three-dimensional point cloud generation module 308, the three-dimensional point cloud of the target point can provide information of more dimensions of the target point, and more accurate positioning is facilitated.

A third aspect of the embodiments of the present application provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor implements the steps of the method for generating a three-dimensional point cloud of a target object based on radar provided by the first aspect of the embodiments of the present application when executing the computer program.

A fourth aspect of the embodiments of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the method for generating a three-dimensional point cloud of a target object based on radar provided by the first aspect of the embodiments of the present application.

It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned functions may be distributed as different functional units and modules according to needs, that is, the internal structure of the apparatus may be divided into different functional units or modules to implement all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.

Those of ordinary skill in the art would appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the above modules or units is only one logical division, and the actual implementation may be implemented by another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed.

The integrated modules/units described above, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above may be implemented by a computer program, which may be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. The computer program includes computer program code, and the computer program code may be in a source code form, an object code form, an executable file or some intermediate form. The computer readable medium may include: any entity or device capable of carrying the above-mentioned computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier signal, telecommunication signal, software distribution medium, etc. It should be noted that the contents contained in the computer-readable storage medium can be increased or decreased as required by legislation and patent practice in the jurisdiction.

The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present application, and they should be construed as being included therein.