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CN115267785A - Speed ambiguity resolving method and system based on TDM MIMO radar - Google Patents

Speed ambiguity resolving method and system based on TDM MIMO radar Download PDF

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CN115267785A
CN115267785A CN202210894799.8A CN202210894799A CN115267785A CN 115267785 A CN115267785 A CN 115267785A CN 202210894799 A CN202210894799 A CN 202210894799A CN 115267785 A CN115267785 A CN 115267785A
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target
speed
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CN115267785B (en
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沈青山
王青波
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Nanjing University of Aeronautics and Astronautics
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
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    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
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    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/50—Systems of measurement based on relative movement of target
    • G01S13/58—Velocity or trajectory determination systems; Sense-of-movement determination systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
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    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
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Abstract

本发明公开了一种基于TDMMIMO雷达的速度解模糊方法及系统。该方法包括：基于虚拟天线阵列数据计算相位校准矩阵；基于相位校准矩阵对实际目标的虚拟天线阵列进行校准；分别对校准后的发射天线序列和接收天线阵列进行求相位角和解缠绕处理；基于发射天线相位序列和接收天线相位序列，分别计算相邻发射天线相位差的均值和相邻接收天线相位差的均值；根据目标速度的估计值计算相位变化；基于相邻发射天线相位差的均值、相邻接收天线相位差的均值以及相位变化计算目标速度的扩展系数；基于扩展系数对目标速度进行解模糊，得到目标实际速度。本发明通过对虚拟天线阵列的相位值进行计算，能够得到速度扩展系数，从而对目前的速度进行扩展。

Figure 202210894799

The invention discloses a speed deblurring method and system based on TDMMIMO radar. The method includes: calculating a phase calibration matrix based on virtual antenna array data; calibrating a virtual antenna array of an actual target based on the phase calibration matrix; performing phase angle and unwinding processing on the calibrated transmitting antenna sequence and receiving antenna array respectively; Antenna phase sequence and receiving antenna phase sequence, calculate the mean value of the phase difference of adjacent transmitting antennas and the mean value of the phase difference of adjacent receiving antennas respectively; calculate the phase change according to the estimated value of the target speed; The average value of the phase difference of the adjacent receiving antennas and the phase change are used to calculate the expansion coefficient of the target velocity; based on the expansion coefficient, the target velocity is de-blurred to obtain the actual target velocity. The present invention can obtain the speed expansion coefficient by calculating the phase value of the virtual antenna array, so as to expand the current speed.

Figure 202210894799

Description

Speed ambiguity resolving method and system based on TDM MIMO radar
Technical Field
The invention relates to the technical field of automotive millimeter wave radars, in particular to a speed ambiguity resolution method and system based on a TDM MIMO radar.
Background
The millimeter wave radar is an electromagnetic wave with the working wavelength in millimeter order, can measure the distance and the speed of a moving target in real time, and is an indispensable sensor component in an automatic driving system. The millimeter wave radar has the characteristics of being long in detectable range, high in measurement real-time performance, free of influence of severe weather such as dust, haze and the like, capable of supporting all-weather work and the like. Generally, automotive radars are required to have high resolution, low cost, and small size. The angular resolution of the radar is directly related to the number of array elements, and the more the number of array elements is, the higher the angular resolution of the radar can be realized. In modern radars, the number of virtual channels of the radar is generally increased by MIMO technology, thereby improving the angular resolution of the radar.
The MIMO radar has a plurality of transmitting antennas and a plurality of receiving antennas, and in order to distinguish data of the respective transmitting antennas among the different receiving antennas, the transmitting antennas need to transmit mutually orthogonal waveforms. Currently, the common MIMO orthogonal design includes Time Division Multiplexing (TDM), frequency Division Multiplexing (FDM), doppler Dimension Multiplexing (DDM), and Code Division Multiplexing (CDM). The TDM MIMO has the characteristics of lowest realization complexity, good orthogonality, low side lobe of distance and speed and the like. And each transmitting antenna in the TDM MIMO radar works in turn to realize orthogonality in time. The disadvantage of this mode of operation is also obvious, one is that the transmit powers of multiple antennas cannot be superimposed, and the other is that the unambiguous velocity range is limited.
The MIMO radar realizes speed measurement and can emit NDopplerA space is TcIs used to generate the chirp. Each reflected chirp is processed by a range Fast Fourier Transform (FFT) to enable detection of the range of the object. Corresponding to N at the same distancedThe individual chirps will peak at the same location, with the peaks having different phases. The phase difference phi corresponds to the velocity v of the object motion, and the phase difference and the velocity have the following corresponding relation:
v＝λφ/(4πTc)
where λ is the operating wavelength of the radar.
Since the velocity measurement is based on the phase difference, ambiguity can arise. This measurement is only unambiguous at | φ | < π, so the maximum measurable speed of the MIMO radar is:
vmax＝λ/Tc
in TDM MIMO automobile radar, due to NTXThe transmitting antennas work in turn, and the actual time interval of two linear frequency modulation pulses is NTXTcThe maximum measurable speed is:
vmax-TDM＝λ/(NTXTc)
according to the analysis, the TDM MIMO automobile radar realizes waveform orthogonality through alternate work of transmitting antennas, but the work mode can reduce the maximum speed measuring range of the radar by NTXAnd (4) multiplying. Therefore, it is very important to research the speed ambiguity-resolving method of the TDM MIMO automobile radar and improve the maximum measurable speed of the radar.
Disclosure of Invention
The invention aims to provide a speed ambiguity-resolving method and system based on a TDM MIMO radar.
In order to achieve the purpose, the invention provides the following scheme:
a speed deblurring method based on a TDM MIMO radar comprises the following steps:
collecting target data through a TDM MIMO automobile radar; the TDM MIMO automotive radar comprises a plurality of receiving antennas and a plurality of transmitting antennas;
performing distance FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of a target;
calculating a phase calibration matrix based on the virtual antenna array data;
calibrating the virtual antenna array of the actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array comprises a calibrated transmitting antenna sequence and a calibrated receiving antenna array;
respectively carrying out phase angle solving and unwrapping processing on the calibrated transmitting antenna sequence and the calibrated receiving antenna array to obtain a transmitting antenna phase sequence and a receiving antenna phase sequence;
respectively calculating the average value of the phase difference of the adjacent transmitting antennas and the average value of the phase difference of the adjacent receiving antennas on the basis of the transmitting antenna phase sequence and the receiving antenna phase sequence;
calculating phase change according to the estimated value of the target speed; the estimated value of the target speed is determined by the Doppler FFT processing result of the target data;
calculating an expansion coefficient of the target speed based on the average of the phase differences of the adjacent transmitting antennas, the average of the phase differences of the adjacent receiving antennas and the phase change;
and resolving the ambiguity of the target speed based on the expansion coefficient to obtain the actual target speed.
Alternatively, by the formula phiTX(j)＝unwrap(angle(STX(j))),1≤j≤NRXPerforming phase angle solving and unwrapping processing on the calibrated transmitting antenna sequence to obtain a transmitting antenna phase sequence;
by the formula phiRX(i)＝unwrap(angle(SRX(i))),1≤i≤NTXPerforming phase angle solving and unwrapping processing on the calibrated receiving antenna array to obtain a receiving antenna phase sequence;
wherein phi isTX(j) Representing the phase sequence, S, of the ith transmit antennaTX(j) Representing the calibrated transmit antenna sequence, NRXIndicating the number of receiving antennas, phiRX(i) Representing the phase sequence of the jth receiving antenna, SRX(i) Representing the calibrated sequence of receiving antennas, NTXIndicating the number of transmit and receive antennas.
Optionally, the mean value of the phase differences of the adjacent transmitting antennas istThe calculation formula is as follows:
Figure BDA0003768945760000031
optionally, the mean value of the phase differences of the adjacent receiving antennas isrThe calculation formula is as follows:
Figure BDA0003768945760000032
optionally, the phase change isdetThe calculation formula of (a) is as follows:
Figure BDA0003768945760000033
wherein v isdetDenotes the estimated value of the target speed, lambda denotes the operating wavelength of the TDM MIMO automotive radar, TcRepresenting the period of the chirp, NTXIndicating the number of transmit and receive antennas.
Optionally, the expansion coefficient n is calculated as follows:
Figure BDA0003768945760000034
wherein, NTXIndicating the number of transmitting and receiving antennas, phidetIndicates a change in phase, phirMeans, phi, representing phase differences of adjacent receiving antennastRepresenting the average of the phase differences of adjacent transmit antennas.
Alternatively, the calculation formula of the target actual speed v is as follows:
v＝vdet+2round(n)vmax
wherein v isdetAn estimated value representing a target velocity, n represents an expansion coefficient, vmaxRepresenting the target speed maximum.
The invention also provides a speed ambiguity-resolving system based on the TDM MIMO radar, which comprises:
the target data acquisition module is used for acquiring target data through the TDM MIMO automobile radar; the TDM MIMO automotive radar comprises a plurality of receiving antennas and a plurality of transmitting antennas;
the processing module is used for carrying out distance FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of a target;
a phase calibration matrix calculation module for calculating a phase calibration matrix based on the virtual antenna array data;
the calibration module is used for calibrating the virtual antenna array of the actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array comprises a calibrated transmitting antenna sequence and a calibrated receiving antenna array;
the antenna phase sequence determining module is used for respectively carrying out phase angle solving and unwrapping processing on the calibrated transmitting antenna sequence and the calibrated receiving antenna array to obtain a transmitting antenna phase sequence and a receiving antenna phase sequence;
the mean value calculation module of the adjacent antenna phase difference is used for respectively calculating the mean value of the adjacent transmitting antenna phase difference and the mean value of the adjacent receiving antenna phase difference based on the transmitting antenna phase sequence and the receiving antenna phase sequence;
the phase change calculation module is used for calculating phase change according to the estimated value of the target speed; the estimated value of the target speed is determined by the Doppler FFT processing result of the target data;
an expansion coefficient calculation module, configured to calculate an expansion coefficient of the target speed based on the average of the phase differences between the adjacent transmitting antennas, the average of the phase differences between the adjacent receiving antennas, and the phase change;
and the target actual speed determining module is used for performing deblurring on the target speed based on the expansion coefficient to obtain the target actual speed.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention accurately estimates the real speed value of any angle target by fully utilizing the phase value of the virtual antenna array, enlarges the maximum speed measurement range of the TDM MIMO automobile radar, achieves the same speed measurement range as that of a single transmitting antenna, and simultaneously ensures the accuracy of azimuth angle estimation. The method has low calculation complexity, does not need to calculate the angle FFT for multiple times, and then compares peak values to carry out speed expansion; the speed of the target at any angle can be expanded, and the target is not limited to the target right in front of the radar.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a velocity disambiguation method based on a TDM MIMO radar according to the present invention;
FIG. 2 is a schematic diagram of an antenna arrangement for a TDM MIMO automotive radar according to the present invention;
FIG. 3 is a schematic diagram of the wave path difference of the TDM MIMO automobile radar receiving antenna provided by the present invention;
FIG. 4 is a timing diagram of the emission of the transmitting antenna of the TDM MIMO automotive radar provided by the present invention;
FIG. 5 is a phase diagram of a virtual antenna array with a target directly in front of the radar, using 12-shot and 8-shot as an example
Fig. 6 is a phase diagram of a virtual antenna array when the target and the radar form a certain angle, taking 12-transmit and 8-receive as an example;
FIG. 7 is a diagram of the speed expansion result of the method provided by the present invention when the target speed changes, taking 12 transmitting antennas as an example, in the diagram, the cross mark represents the unexpanded result, and the circular mark represents the expanded result;
fig. 8 is a diagram of the speed expansion result of the method provided by the present invention when the target angle changes, taking 12 transmitting antennas as an example, in the diagram, the cross mark represents the unexpanded result, and the circular mark represents the expanded result.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
The invention aims to provide a speed ambiguity-resolving method and system based on a TDM MIMO radar.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
The specific position of a radar target is generally determined by radial distance, azimuth angle and pitch angle, and the TDM MIMO automobile radar comprises N in the horizontal direction for accurately measuring the azimuth angle information of the targetTXA transmitting antenna and NRXA receiving antenna; there will also be a small number of transmit antennas in the vertical direction to measure the pitch angle information of the target. In order to accurately estimate the actual speed of the target, the invention uses an antenna array in the horizontal direction to perform speed ambiguity resolution.
In the TDM MIMO automotive radar, the transmitting antenna and the receiving antenna array generally adopt an equally spaced design pattern, as shown in fig. 2, NTXThe distance between every two adjacent antennas in each transmitting antenna is dt，NRXThe distance between every two adjacent antennas in each receiving antenna is dr. To NTXA transmitting antenna numbered 1 to NTX(ii) a To NRXA receiving antenna numbered 1 to NRX. In practical design, the spacing between some adjacent receiving antennas may be set to other values to realize a larger number of virtual antenna arrays, and this part of data may not be used or may be subjected to additional processing, which does not affect the present invention.
The MIMO automobile radar under the TDM working mode realizes the orthogonality of the transmitting antenna in time, NTXNumber 1 to number N of transmitting antennaTXSequential emission, NRXThe receiving antennas simultaneously receive the echo of each transmitting antenna to form NTX×NRXThe echo signal array of (1).
The radar carries out frequency mixing processing on the transmitting signal and the receiving signal to obtain an intermediate frequency signal, and then the intermediate frequency signal is sampled by the ADC to obtain a discrete signal sequence. TDM MIMO steamThe radar of the vehicle is in a chirp period TCInternal sampling NRangeSub, NTXThe transmitting antennas transmit signals in sequence in a cycle; one frame carries out NDopplerThe secondary circulation is used for achieving the purpose of speed measurement. One frame of radar data may be represented as NRange×NDoppler×NTX× NRXThe four-dimensional array of (1).
In NRangePerforming distance FFT processing on the dimension, and distinguishing targets in the radial distance; index Ind of a certain distancerIf the FFT result of the lower distance has a peak value, the target exists at the distance, and the specific distance value can be calculated by the distance index, wherein Ind is more than or equal to 1r≤NRange. After the distance FFT processing, N under each distance index is obtainedDopplerDimension is processed by Doppler FFT with a certain Doppler index InddIf a peak value exists in the Doppler FFT result, the target with the corresponding speed exists, and the specific speed value can be calculated by the Doppler index, wherein Ind is more than or equal to 1d≤NDoppler. For range-Doppler two-dimensional data, a certain range-Doppler index (Ind)r,Indd) If there is a peak, it indicates that there is a target with corresponding speed at the distance, and N of the targetTX×NRXVirtual antenna array data is thus available.
As shown in fig. 1, the speed deblurring method based on the TDM MIMO radar provided by the present invention includes:
step 101: collecting target data through a TDM MIMO automobile radar; the TDM MIMO automotive radar includes a plurality of receive antennas and a plurality of transmit antennas.
In an open field or a microwave darkroom environment, the TDM MIMO automobile radar is used for collecting static target data at a certain distance in front of the automobile radar.
Step 102: and performing distance FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of the target.
Step 103: a phase calibration matrix is calculated based on the virtual antenna array data.
Over-distance FFT sumObtaining N of the target after Doppler FFT processingTX×NRXVirtual antenna array data Scalib. Selecting antenna pair data S of transmitting antenna 1-receiving antenna 1calib(1,1) as a reference, a phase calibration matrix is calculated:
Figure BDA0003768945760000071
the matrix is used to calibrate the phase values of the virtual antenna array to compensate for amplitude and phase mismatches caused by antenna path length mismatch, inter-chip differences, antenna coupling, etc.
Step 104: calibrating the virtual antenna array of the actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array comprises a calibrated transmitting antenna sequence and a calibrated receiving antenna array.
The TDM MIMO automobile radar obtains four-dimensional array data in an actual working environment, and distance and speed values of a plurality of actual targets are obtained after constant false alarm screening. The resulting speed values may be ambiguous due to the speed ambiguity associated with the TDM mode of operation. Virtual antenna array data S for real targetvirtualProcessing is carried out to obtain a real speed value of the target, and the virtual antenna array data is calibrated according to the calibration matrix obtained in the step 103:
S(i,j)＝Svirtual(i,j)×phasecalib(i,j),1≤i≤NTX,1≤j≤NRX (2)
step 105: and respectively carrying out phase angle solving and unwrapping processing on the calibrated transmitting antenna sequence and the calibrated receiving antenna array to obtain a transmitting antenna phase sequence and a receiving antenna phase sequence.
All receiving antenna sequences S for the ith transmitting antennaRX(i)＝[S(i,1)S(i,2)…S(i,NRX)]And performing phase angle solving and unwrapping operations to obtain a phase sequence of the receiving antenna:
φRX(i)＝unwrap(angle(SRX(i))),1≤i≤NTX (3)
all transmitting antenna sequences S for the jth receiving antennaTX(i)＝[S(1,j)S(2,j)…S(NTX,j)]And performing phase angle solving and unwrapping operations to obtain a phase sequence of the transmitting antenna:
φTX(j)＝unwrap(angle(STX(j))),1≤j≤NRX (4)
the phase sequence obtained after the processing is shown in fig. 5 and 6, and an example is a 12-transmission 8-reception automotive radar. The different colors in the figure represent 12 different transmitting antennas, and the same color represents 8 receiving antennas corresponding to the same transmitting antenna. FIG. 5 is a phase sequence of the object moving in front of Lei Dazheng; fig. 6 is a phase sequence with the target at an angle to the radar.
Step 106: and respectively calculating the average value of the phase difference of the adjacent transmitting antennas and the average value of the phase difference of the adjacent receiving antennas on the basis of the transmitting antenna phase sequence and the receiving antenna phase sequence.
Calculating the transmitting antenna sequence phi in turnTX(j) And (3) solving the average value of the phase difference values of the adjacent antennas to obtain the average value of the phase difference values of the adjacent transmitting antennas:
Figure BDA0003768945760000081
calculating in sequence a sequence of receiving antennas phiRX(i) And (3) solving the average value of the phase difference values of the adjacent antennas to obtain the average value of the phase difference values of the adjacent receiving antennas:
Figure BDA0003768945760000082
step 107: calculating phase change according to the estimated value of the target speed; the estimate of the target velocity is determined from the doppler FFT processing of the target data.
Based on the Doppler FFT result of the target data, a predicted value v of the target speed can be obtaineddetThe velocity being caused by the time interval between two chirps of the same transmit antennaThe phase difference change is:
Figure BDA0003768945760000083
step 108: and calculating the expansion coefficient of the target speed based on the average value of the phase differences of the adjacent transmitting antennas, the average value of the phase differences of the adjacent receiving antennas and the phase change.
As shown in fig. 3, when the target moves in front of the radar at a speed v and the angle between the target and the radar is θ, for all receiving antennas of the same transmitting antenna, the echo between two adjacent receiving antennas has drsin θ, which corresponds to the phase change of the receiving antenna:
Figure BDA0003768945760000091
where λ is the operating wavelength of the radar and can be represented by λ = c/fcIs obtained, c is the speed of light, fcIs the operating frequency of the radar.
As shown in fig. 4, for all transmitting antennas of the same receiving antenna, the echo path difference between two adjacent transmitting antennas is composed of two parts, one part is the path difference caused by the transmitting antenna spacing, and this part reflects the azimuth angle of the target, and the corresponding phase changes:
Figure BDA0003768945760000092
another part is the phase change caused by the object motion, and the object moves by vT in the interval time of two adjacent transmitting antennascThis part reflects the velocity change of the target, the corresponding phase change is:
Figure BDA0003768945760000093
the actual phase change of two adjacent transmit antennas then becomes:
Figure BDA0003768945760000094
in combination of equations (8) and (11), the adjacent antenna phase change due to velocity is:
Figure BDA0003768945760000095
when phi isdetWhen the value of (d) exceeds. + -. π, the velocity is blurred. N is used for representing the number of turns of phase ambiguity, namely a speed expansion coefficient, and when the speed expansion coefficient is positive, the speed is positive, namely the target is gradually far away from the radar; when the velocity expansion coefficient is negative, it means that the velocity is negative, i.e., the target gradually approaches the radar. The true phase difference can be expressed as:
φtrue＝φdet+2nπ,n∈[1-NTX,NTX-1] (13)
this phase difference can be equated to N in the same cycleTXSum of phase differences of the transmit antennas caused by velocity:
φtrue＝NTXφt-v (14)
combining equation (7) and equations (12) to (14), the velocity expansion coefficient can be obtained as:
Figure BDA0003768945760000101
step 109: and performing deblurring on the target speed based on the expansion coefficient to obtain the target actual speed.
v＝vdet+2round(n)vmax (15)
Where round (n) denotes rounding n.
Deblurring results as shown in fig. 7 and 8, taking the car radar of 12-transmission and 8-reception as an example, the fork marks represent the initial doppler FFT results,the circular marks represent deblurring results. Fig. 7 shows the deblurring result when the moving speed of the target changes, and the algorithm can obtain the actual speed. FIG. 8 shows the target at different angles θ1De-blurring result when moving forward at a speed of 10m/s, actual radial velocity v measured by radar1Can be expressed as v1＝10cosθ1And the result obtained by the fuzzy algorithm solution is consistent with the theoretical result.
After the accurate speed of the target is obtained, the phase of the virtual antenna array can be compensated, so that a more accurate azimuth angle estimation value is obtained.
According to the invention, the speed expansion coefficient can be obtained by calculating the phase value of the virtual antenna array, so that the current speed is expanded to reach the speed measuring range same as that of a single-transmitting multi-receiving antenna, the problem that the speed measuring range is obviously reduced when the number of transmitting antennas of the TDM MIMO automobile radar is large is solved, and the speeds of targets with different azimuth angles can be accurately expanded.
The invention also provides a speed ambiguity resolving system based on the TDM MIMO radar, which comprises the following components:
the target data acquisition module is used for acquiring target data through the TDM MIMO automobile radar; the TDM MIMO automotive radar comprises a plurality of receiving antennas and a plurality of transmitting antennas;
the processing module is used for carrying out distance FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of a target;
a phase calibration matrix calculation module for calculating a phase calibration matrix based on the virtual antenna array data;
the calibration module is used for calibrating the virtual antenna array of the actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array comprises a calibrated transmitting antenna sequence and a calibrated receiving antenna array;
the antenna phase sequence determining module is used for respectively carrying out phase angle solving and unwrapping processing on the calibrated transmitting antenna sequence and the calibrated receiving antenna array to obtain a transmitting antenna phase sequence and a receiving antenna phase sequence;
the mean value calculation module of the adjacent antenna phase difference is used for respectively calculating the mean value of the adjacent transmitting antenna phase difference and the mean value of the adjacent receiving antenna phase difference based on the transmitting antenna phase sequence and the receiving antenna phase sequence;
the phase change calculation module is used for calculating phase change according to the estimated value of the target speed; the estimated value of the target speed is determined by the Doppler FFT processing result of the target data;
an expansion coefficient calculation module for calculating an expansion coefficient of the target speed based on the average of the phase differences of the adjacent transmitting antennas, the average of the phase differences of the adjacent receiving antennas, and the phase variation;
and the target actual speed determining module is used for performing deblurring on the target speed based on the expansion coefficient to obtain the target actual speed.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (8)

1.一种基于TDM MIMO雷达的速度解模糊方法，其特征在于，包括：1. A velocity defuzzification method based on TDM MIMO radar, it is characterized in that, comprising: 通过TDM MIMO汽车雷达采集目标数据；所述TDM MIMO汽车雷达包括多个接收天线和多个发射天线；Collecting target data through TDM MIMO automotive radar; the TDM MIMO automotive radar includes multiple receiving antennas and multiple transmitting antennas; 对所述目标数据进行距离FFT和多普勒FFT处理，得到目标的虚拟天线阵列数据；Perform range FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of the target; 基于所述虚拟天线阵列数据计算相位校准矩阵；calculating a phase calibration matrix based on the virtual antenna array data; 基于所述相位校准矩阵对实际目标的虚拟天线阵列进行校准，得到校准后的虚拟天线阵列；所述校准后的虚拟天线阵列包括校准后的发射天线序列和接收天线阵列；Calibrate the virtual antenna array of the actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array includes a calibrated transmit antenna sequence and a receive antenna array; 分别对校准后的发射天线序列和接收天线阵列进行求相位角和解缠绕处理，得到发射天线相位序列和接收天线相位序列；Calculate the phase angle and unwrap the calibrated transmit antenna sequence and receive antenna array respectively to obtain the transmit antenna phase sequence and receive antenna phase sequence; 基于所述发射天线相位序列和所述接收天线相位序列，分别计算相邻发射天线相位差的均值和相邻接收天线相位差的均值；Based on the transmitting antenna phase sequence and the receiving antenna phase sequence, calculate the mean value of the phase difference between adjacent transmitting antennas and the mean value of the phase difference between adjacent receiving antennas; 根据目标速度的估计值计算相位变化；所述目标速度的估计值由所述目标数据的多普勒FFT处理结果确定；calculating the phase change based on an estimated value of the target velocity; the estimated value of the target velocity is determined by a Doppler FFT processing result of the target data; 基于所述相邻发射天线相位差的均值、所述相邻接收天线相位差的均值以及所述相位变化计算所述目标速度的扩展系数；calculating a spreading factor for the target velocity based on the mean value of the phase difference of the adjacent transmit antennas, the mean value of the phase difference of the adjacent receive antennas, and the phase change; 基于所述扩展系数对所述目标速度进行解模糊，得到目标实际速度。The target speed is defuzzified based on the expansion coefficient to obtain the target actual speed. 2.根据权利要求1所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，通过公式φTX(j)＝unwrap(angle{STX(j)))，1≤j≤NRX对校准后的发射天线序列进行求相位角和解缠绕处理，得到发射天线相位序列；2. the speed deambiguation method based on TDM MIMO radar according to claim 1, is characterized in that, by formula φ TX (j)=unwrap (angle{S TX (j))), 1≤j≤N RX pairs Calculate the phase angle and unwrap the calibrated transmit antenna sequence to obtain the transmit antenna phase sequence; 通过公式φRX(i)＝unwrap(angle(SRX(i)))，1≤i≤NTX对校准后的接收天线阵列进行求相位角和解缠绕处理，得到接收天线相位序列；Through the formula φ RX (i)=unwrap(angle(S RX (i))), 1≤i≤N TX calculates the phase angle and unwraps the calibrated receiving antenna array to obtain the receiving antenna phase sequence; 其中，φTX(j)表示第i个发射天线的相位序列，STX(j)表示校准后的发射天线序列，NRX表示接收天线的个数，φRX(i)表示第j个接收天线的相位序列，SRX(i)表示校准后的接收天线序列，NTX表示发射收天线的个数。Among them, φ TX (j) represents the phase sequence of the i-th transmitting antenna, S TX (j) represents the calibrated transmitting antenna sequence, N RX represents the number of receiving antennas, and φ RX (i) represents the j-th receiving antenna , S RX (i) represents the calibrated receiving antenna sequence, and N TX represents the number of transmitting and receiving antennas. 3.根据权利要求2所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，所述相邻发射天线相位差的均值φt计算公式如下：3. the speed defuzzification method based on TDM MIMO radar according to claim 2, is characterized in that, the mean value φ t calculation formula of described adjacent transmitting antenna phase difference is as follows:
Figure FDA0003768945750000021
Figure FDA0003768945750000021
 4.根据权利要求2所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，所述相邻接收天线相位差的均值φr计算公式如下：4. the speed deambiguation method based on TDM MIMO radar according to claim 2, is characterized in that, the mean value φ r calculation formula of described adjacent receiving antenna phase difference is as follows:
Figure FDA0003768945750000022
Figure FDA0003768945750000022
 5.根据权利要求1所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，所述相位变化φdet的计算公式如下：5. the speed defuzzification method based on TDM MIMO radar according to claim 1, is characterized in that, the computing formula of described phase change φ det is as follows:
Figure FDA0003768945750000023
Figure FDA0003768945750000023
 其中，vdet表示目标速度的估计值，λ表示TDM MIMO汽车雷达的工作波长，Tc表示线性调频脉冲周期，NTX表示发射收天线的个数。Among them, v det represents the estimated value of the target velocity, λ represents the operating wavelength of the TDM MIMO automotive radar, T c represents the chirp cycle, and N TX represents the number of transmitting and receiving antennas. 6.根据权利要求1所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，其特征在于，所述扩展系数n的计算公式如下：6. the speed defuzzification method based on TDM MIMO radar according to claim 1, is characterized in that, the calculation formula of described expansion coefficient n is as follows:
Figure FDA0003768945750000024
Figure FDA0003768945750000024
 其中，NTX表示发射收天线的个数，φdet表示相位变化，φr表示相邻接收天线相位差的均值，φt表示相邻发射天线相位差的均值。Among them, N TX represents the number of transmitting and receiving antennas, φ det represents the phase change, φ r represents the mean value of the phase difference between adjacent receiving antennas, and φ t represents the mean value of the phase difference between adjacent transmitting antennas. 7.根据权利要求1所述的基于TDM MIMO雷达的速度解模糊方法，其特征在于，其特征在于，所述目标实际速度v的计算公式如下：7. the velocity defuzzification method based on TDM MIMO radar according to claim 1, is characterized in that, the calculation formula of described target actual velocity v is as follows: v＝vdet+2round(n)vmax v=v det +2round(n)v max 其中，vdet表示目标速度的估计值，n表示扩展系数，vmax表示目标速度最大值。Among them, v det represents the estimated value of the target speed, n represents the expansion coefficient, and v max represents the maximum value of the target speed. 8.一种基于TDM MIMO雷达的速度解模糊系统，其特征在于，包括：8. A speed defuzzification system based on TDM MIMO radar, characterized in that, comprising: 目标数据采集模块，用于通过TDM MIMO汽车雷达采集目标数据；所述TDM MIMO汽车雷达包括多个接收天线和多个发射天线；A target data acquisition module, configured to collect target data through a TDM MIMO automotive radar; the TDM MIMO automotive radar includes multiple receiving antennas and multiple transmitting antennas; 处理模块，用于对所述目标数据进行距离FFT和多普勒FFT处理，得到目标的虚拟天线阵列数据；A processing module, configured to perform range FFT and Doppler FFT processing on the target data to obtain virtual antenna array data of the target; 相位校准矩阵计算模块，用于基于所述虚拟天线阵列数据计算相位校准矩阵；A phase calibration matrix calculation module, configured to calculate a phase calibration matrix based on the virtual antenna array data; 校准模块，用于基于所述相位校准矩阵对实际目标的虚拟天线阵列进行校准，得到校准后的虚拟天线阵列；所述校准后的虚拟天线阵列包括校准后的发射天线序列和接收天线阵列；A calibration module, configured to calibrate a virtual antenna array of an actual target based on the phase calibration matrix to obtain a calibrated virtual antenna array; the calibrated virtual antenna array includes a calibrated transmit antenna sequence and a receive antenna array; 天线相位序列确定模块，用于分别对校准后的发射天线序列和接收天线阵列进行求相位角和解缠绕处理，得到发射天线相位序列和接收天线相位序列；The antenna phase sequence determination module is used to calculate the phase angle and unwrap the calibrated transmitting antenna sequence and receiving antenna array respectively to obtain the transmitting antenna phase sequence and the receiving antenna phase sequence; 相邻天线相位差的均值计算模块，用于基于所述发射天线相位序列和所述接收天线相位序列，分别计算相邻发射天线相位差的均值和相邻接收天线相位差的均值；The mean value calculation module of the phase difference of adjacent antennas is used to calculate the mean value of the phase difference of adjacent transmitting antennas and the mean value of the phase difference of adjacent receiving antennas based on the phase sequence of the transmitting antenna and the phase sequence of the receiving antenna; 相位变化计算模块，用于根据目标速度的估计值计算相位变化；所述目标速度的估计值由所述目标数据的多普勒FFT处理结果确定；The phase change calculation module is used to calculate the phase change according to the estimated value of the target speed; the estimated value of the target speed is determined by the Doppler FFT processing result of the target data; 扩展系数计算模块，用于基于所述相邻发射天线相位差的均值、所述相邻接收天线相位差的均值以及所述相位变化计算所述目标速度的扩展系数；An expansion coefficient calculation module, configured to calculate the expansion coefficient of the target speed based on the mean value of the phase difference of the adjacent transmitting antennas, the mean value of the phase difference of the adjacent receiving antennas, and the phase change; 目标实际速度确定模块，用于基于所述扩展系数对所述目标速度进行解模糊，得到目标实际速度。A target actual speed determination module, configured to defuzzify the target speed based on the expansion coefficient to obtain the target actual speed.
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