Radar channel calibration method and device and storage medium

Abstract

The invention provides a radar channel calibration method and device and a storage medium, and aims to form a second array steering vector matrix by establishing a signal model without channel amplitude and phase errors and only with roll errors. And constructing a multivariable optimization problem according to the relationship among the first array steering vector matrix, the amplitude-phase calibration coefficient of the multiple channels of the radar and the first-order Taylor expression of the second array steering vector matrix, and solving the original problem by adopting an iterative alternating minimization-based optimization algorithm. Therefore, the influence caused by the roll error in the radar darkroom calibration process can be eliminated. The estimated multi-channel amplitude-phase calibration coefficient and the roll error are decoupled, that is, the calibration coefficient can truly reflect the channel amplitude-phase error. In addition, a bubble level does not need to be used for fine adjustment of roll errors before calibration, only rough adjustment is needed, and finally automatic compensation is conducted through a calibration algorithm.

Description

Technical Field

[0001] The present invention relates to the field of radar technology, and in particular to a radar channel calibration method, device and storage medium. Background Art

[0002] Due to the influence of factors such as antenna processing errors, feeder line length errors, and antenna mutual coupling, the radar's multi-channels have inconsistent amplitudes and phases, resulting in errors in the radar's direction-finding results, or even direction-finding errors. Therefore, in order to realize the radar's direction-finding function, it is necessary to calibrate the radar's multi-channels for amplitude and phase. Amplitude and phase calibration needs to be performed in a darkroom. By placing angular invertors at multiple known angles and collecting radar data at the same time, the amplitude and phase calibration coefficients of each channel can be estimated.

[0003] During the darkroom calibration process, it is generally necessary to ensure that the radar is in a horizontal state. The common method is to use a bubble level to make fine adjustments. However, if the radar itself is small in size, there will still be an error of a few tenths to a few degrees between the horizontal plane of the radar and the standard horizontal plane after adjustment with a bubble level. This error can be divided into pitch error and roll error. The pitch error can be reduced by laser irradiation combined with mirror reflection, but the roll error is difficult to reduce.

[0004] Since the existing bubble level adjustment cannot ensure that the radar is in the standard horizontal plane, the radar roll error is difficult to eliminate. Therefore, the channel amplitude and phase calibration coefficients obtained in the presence of roll error are coupled with the roll error and cannot truly reflect the channel amplitude and phase errors, resulting in the direction finding error caused by the roll error in the calibrated radar. Summary of the invention

[0005] The present invention provides a radar channel calibration method, device and storage medium, aiming to effectively solve the technical problems in the prior art that radar channel calibration is difficult and the calibrated radar has a direction finding error caused by a rolling error.

[0006] According to one aspect of the present invention, the present invention provides a radar channel calibration method, wherein the radar comprises at least one transmitting antenna and at least one receiving antenna, wherein the at least one transmitting antenna and the at least one receiving antenna constitute a plurality of channels, and the method comprises:

[0007] Step S1, driving the servo carrying the radar in the darkroom to rotate so that the target angle reflector is located at multiple azimuth and elevation angles of the radar respectively, the radar transmits a radar test signal at each azimuth and elevation angle respectively, and for each azimuth and elevation angle, obtaining an echo signal fed back by the target angle reflector to the radar test signal and extracting a first array steering vector matrix corresponding to the target angle reflector;

[0008] Step S2, establish a signal model without channel amplitude-phase error and only with roll error to construct a second array steering vector matrix, and perform a first-order Taylor expansion on the second array steering vector matrix when the roll error of the radar is lower than a preset value to obtain a first-order Taylor expression containing the roll error;

[0009] Step S3, construct a multi-variable optimization problem according to the relationship between the first array steering vector matrix, the amplitude-phase calibration coefficients of multiple channels of the radar, and the first-order Taylor expression of the second array steering vector matrix;

[0010] Step S4, use an optimization algorithm based on iterative alternating minimization to solve the original problem to obtain the estimated values of the amplitude-phase calibration coefficients and the roll error of multiple channels of the radar.

[0011] Further, the sub-steps in Step S2 include:

[0012] Step S21, use a bubble level to adjust the roll error of the radar to be lower than the preset value;

[0013] Step S22, establish a signal model without channel amplitude-phase error and only with roll error, specifically:

[0014] A t =[a1,a2,...,a L ;

[0015] where a l is the array steering vector of the l-th array without channel amplitude-phase error and with roll error, 0 < l ≤ L, and l is a positive integer;

[0016] Step S23, perform a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression containing the roll error, specifically:

[0017] A t ≈A i +A′ i Δγ;

[0018] where, A t is the second array steering vector matrix, A i is the ideal array manifold without channel amplitude-phase error and without roll error, A′ i is the derivative of A i with respect to the roll error, and Δγ is the roll error of multiple channels of the radar.

[0019] Further, in Step S3, the sub-steps of the process of constructing the multi-variable optimization problem include:

[0020] Step S31, design the following optimal estimator:

[0021]

[0022] Among them, A m is the first array steering vector matrix, diag(·) represents a diagonal matrix formed by vectors, η is the amplitude and phase calibration coefficient of the radar multi-channel, ||·|| F represents the F-norm.

[0023] Furthermore, in step S4, an optimization algorithm based on iterative alternating minimization is used to solve the original problem, and the estimated values ​​of the amplitude and phase calibration coefficients and the rolling error of the radar multi-channel are obtained, including:

[0024] By solving the two unknown parameters η and Δγ in the optimization estimator, the result of the optimization estimator is minimized to obtain the estimated value of the amplitude and phase calibration coefficient of the radar multi-channel and the roll error estimate Use the amplitude and phase calibration coefficients to estimate the value Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true rolling error value.

[0025] Furthermore, in step S4, the original problem is solved by using an optimization algorithm based on iterative alternating minimization to obtain the estimated values ​​of amplitude and phase calibration coefficients and the estimated value of rolling error of the radar multi-channel, and the following is further included:

[0026] Let i=1, where i is the iteration count;

[0027] make Each iteration updates η and Δγ respectively;

[0028] Among them, η is the amplitude and phase calibration coefficient of the radar multi-channel, Δγ is the roll error of the radar multi-channel, is the estimated value of the amplitude and phase calibration coefficients of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0029] Further, in step S1, before driving the servo carrying the radar in the darkroom to rotate, the method includes:

[0030] The radar is placed on a servo in the darkroom and the target angle is placed normal to the far field position of the radar.

[0031] Furthermore, the multiple azimuth and elevation angles in step S1 are multiple nominal azimuth and elevation angles, which are respectively expressed as: (α1, β1), (α2, β2), …, (α L ,β L );

[0032] The corresponding extracted first array steering vector is expressed as To construct a first array steering vector matrix, the first array steering vector matrix is ​​expressed as:

[0033]

[0034] Among them, A m is the first array steering vector matrix, and L is a positive integer.

[0035] According to another aspect of the present invention, a radar channel calibration device is provided, wherein the radar comprises at least one transmitting antenna and at least one receiving antenna, wherein the at least one transmitting antenna and the at least one receiving antenna constitute a plurality of channels, and the device comprises:

[0036] A driving and echo signal acquisition unit, used for driving the servo carrying the radar in the darkroom to rotate, so that the target angle reflector is located at multiple azimuth and elevation angles of the radar, the radar transmits a radar test signal at each azimuth and elevation angle, and for each azimuth and elevation angle, obtains an echo signal fed back by the target angle reflector to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector;

[0037] a signal model building unit, used for building a signal model without channel amplitude and phase errors and with only rolling error, so as to construct a second array steering vector matrix, and when the rolling error of the radar is lower than a preset value, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including the rolling error;

[0038] An optimization problem construction unit, used for constructing a multivariable optimization problem according to the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and the first-order Taylor expression of the second array steering vector matrix;

[0039] The optimization problem solving unit is used to solve the original problem by using an optimization algorithm based on iterative alternating minimization to obtain the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel.

[0040] According to another aspect of the present invention, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the radar channel calibration method described in any of the above embodiments is implemented.

[0041] Through one or more of the above embodiments of the present invention, at least the following technical effects can be achieved:

[0042] The technical solution disclosed in the present invention aims to establish a signal model without channel amplitude and phase errors and only with roll errors to form a second array steering vector matrix, construct a multivariable optimization problem based on the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel and the first-order Taylor expression of the second array steering vector matrix, and use an optimization algorithm based on iterative alternating minimization to solve the original problem, thereby eliminating the influence of the roll error during the radar darkroom calibration process. The estimated multi-channel amplitude and phase calibration coefficients are decoupled from the roll error, that is, the calibration coefficient can truly reflect the channel amplitude and phase error. In addition, before calibration, there is no need to use a bubble level to fine-tune the roll error, but only a rough adjustment is required, and finally the calibration algorithm automatically compensates. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The technical solutions and other beneficial effects of the present invention will be made apparent by describing in detail the specific embodiments of the present invention in conjunction with the accompanying drawings.

[0044] Figure 1 Schematic diagram of radar array antenna echo signal reception.

[0045] Figure 2 A flowchart of a radar channel calibration method provided by an embodiment of the present invention.

[0046] Figure 3A Channel phase simulation diagram provided by the embodiment of the present invention Figure 1 .

[0047] Figure 3B Channel phase simulation diagram provided by the embodiment of the present invention Figure 2 .

[0048] Figure 4 A schematic diagram of the structure of a radar channel calibration device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0050] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " herein, unless otherwise specified, generally indicates that the associated objects before and after are in an "or" relationship.

[0051] The technical terms involved in the present invention are described below:

[0052] MIMO (Multiple-Input Multiple-Output) technology refers to the use of multiple transmitting antennas and receiving antennas at the transmitting end and receiving end respectively, so that the signal is transmitted on multiple channels, thereby improving the communication quality. It can make full use of spatial resources and achieve multiple transmission and multiple reception through multiple antennas. Without increasing spectrum resources and antenna transmission power, it can multiply the system channel capacity.

[0053] Figure 1 Schematic diagram of radar array antenna echo signal reception.

[0054] like Figure 1 As shown in the figure, under far-field conditions, the phase difference between radar array antennas is caused by the path difference of the target echo signal reaching each array antenna. This phase difference is recorded as Usually and array spacing d m And the target direction of arrival (DOA). The phase difference of the data collected by the radar receiver for each antenna channel is not only caused by the wavelength difference, but also related to the feeder length of each channel. The channel delay phase difference caused by the unequal length of the feeder of each channel, denoted as ε, is not related to the target direction of arrival. Therefore, when ε is superimposed on When the radar is on the ground, it will affect the DOA estimation of the radar to the target. As mentioned in the background, the calibrated radar still has direction finding error caused by the roll error.

[0055] Figure 2 A flowchart of a radar channel calibration method provided by an embodiment of the present invention.

[0056] like Figure 2 As shown, the radar channel calibration method provided by the embodiment of the present invention includes:

[0057] Step S1, driving the servo carrying the radar in the darkroom to rotate so that the target angle reflector is located at multiple azimuth and elevation angles of the radar respectively, the radar transmits a radar test signal at each azimuth and elevation angle respectively, and for each azimuth and elevation angle, obtaining an echo signal fed back by the target angle reflector to the radar test signal and extracting a first array steering vector matrix corresponding to the target angle reflector;

[0058] Step S2, establishing a signal model without channel amplitude and phase errors and with only roll error to construct a second array steering vector matrix, and when the roll error of the radar is lower than a preset value, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including the roll error;

[0059] Step S3, extracting multi-frame multi-channel data corresponding to a moving target that meets the preset association condition and has the strongest signal-to-noise ratio to form a target channel data matrix;

[0060] Step S4, using an optimization algorithm based on iterative alternating minimization to solve the original problem, and obtaining the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel.

[0061] The technical solution disclosed in the present invention can be used for single-transmit multiple-receive radar, multiple-transmit single-receive radar, and MIMO (Multiple-Input Multiple-Output) radar; wherein, MIMO radar refers to a radar with a multiple-transmit multiple-receive antenna system, which provides an economical and effective way to improve the resolution of the radar, and the antenna volume is relatively small. Based on a multi-element antenna, the MIMO radar uses M channels to transmit mutually orthogonal signals, and the multi-waveform signals remain independent in space. After being scattered by the target, they are received by N receiving array elements, and each array element uses M matched filters to match the echo, so that the echo data of M*N channels can be obtained.

[0062] The above steps S1 to S4 are described in detail below.

[0063] In step S1, the servo carrying the radar in the darkroom is driven to rotate so that the target angle reflector is located at multiple azimuth and elevation angles of the radar respectively, and the radar transmits a radar test signal at each azimuth and elevation angle respectively, and for each azimuth and elevation angle, an echo signal fed back by the target angle reflector to the radar test signal is obtained and a first array steering vector matrix corresponding to the target angle reflector is extracted.

[0064] Exemplarily, in a MIMO radar system, a pulse sequence is transmitted in a time-division transmission mode, and the time required for all array antennas to transmit a pulse signal in turn is a Burst cycle (i.e., a pulse sequence cycle), and the time of a Burst cycle is divided into multiple Chirp signal cycles, wherein the multiple Chirp signal cycles within a Burst cycle can be the same or different, and only one antenna transmits a pulse signal in each Chirp signal cycle.

[0065] In the embodiment of the present invention, the multiple azimuth and elevation angles in step S1 are multiple nominal azimuth and elevation angles, which are respectively expressed as: (α1, β1), (α2, β2), …, (α L ,β L ), where L is a positive integer; that is, the servo is rotated to L nominal azimuth and pitch angles, and the L nominal azimuth and pitch angles are respectively expressed as (α1, β1), (α2, β2),…, (α L ,β L ). The radar sends signals at each azimuth and elevation angle and collects baseband data and extracts the first array steering vector corresponding to the target angle; the extracted first array steering vector is expressed as To construct the first array steering vector matrix A m , which is used for the subsequent calculation of the roll error and radar channel amplitude and phase error coefficients. Specifically, let A m To measure the array flow pattern.

[0066] In step S2, a signal model without channel amplitude and phase errors and with only roll error is established to construct a second array steering vector matrix, and when the roll error of the radar is lower than a preset value, a first-order Taylor expansion is performed on the second array steering vector matrix to obtain a first-order Taylor expression including the roll error.

[0067] The sub-steps in step S2 include:

[0068] Step S21, using a bubble level to adjust the roll error of the radar to be lower than a preset value;

[0069] In the embodiment of the present invention, the roll error of the radar can be adjusted to a relatively small value by a bubble level or the like, for example, the roll error is less than 10 degrees, 2 degrees or 1 degree, etc. On the contrary, if the bubble level is not adjusted well, the approximate error will be slightly larger.

[0070] Since the original A tIf it is a non - linear function of Δγ, then when the roll error of the radar is lower than the preset value, it can be Taylor - expanded to obtain a first - order Taylor expression containing the roll error, which is a linear function. Then it is easy to solve for Δγ. That is to say, the purpose of the above first - order Taylor expansion of the second array steering vector matrix is to convert the expression based on the non - linearity of Δγ into a linear expression based on Δγ, so as to facilitate subsequent compensation and calibration processing.

[0071] Step S22: Establish a signal model without channel amplitude - phase error and only with roll error, specifically:

[0072] A t =[a1,a2,...,a L ;

[0073] where a l is the array steering vector of the l - th array without channel amplitude - phase error but with roll error, 0 < l ≤ L, and l is a positive integer

[0074] Step S23: Perform a first - order Taylor expansion on the second array steering vector matrix to obtain a first - order Taylor expression containing the roll error, specifically:

[0075] A t ≈A i +A′ i Δγ;

[0076] where, A t is the second array steering vector matrix, A i is the ideal array manifold without channel amplitude - phase error and without roll error, A′ i is the derivative of A i with respect to the roll error, and Δγ is the roll error of the radar multi - channels. A i can be given according to the radar transmission signal wavelength, array geometry structure, and L known azimuth and elevation angles.

[0077] In step S3, construct a multi - variable optimization problem according to the relationship between the first array steering vector matrix, the amplitude - phase calibration coefficients of the radar multi - channels, and the first - order Taylor expression of the second array steering vector matrix.

[0078] In step S3, the sub - steps of the process of constructing the multi - variable optimization problem include:

[0079] Step S31: Design the following optimal estimator:

[0080]

[0081] where, A mis the first array steering vector matrix, diag(·) represents a diagonal matrix formed by vectors, η is the amplitude and phase calibration coefficient of the radar multi-channel, ||·|| F represents the F-norm.

[0082] In step S4, an optimization algorithm based on iterative alternating minimization is used to solve the original problem, and the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel are obtained.

[0083] By solving the two unknown parameters η and Δγ in the optimization estimator, the result of the optimization estimator is minimized to obtain the estimated value of the amplitude and phase calibration coefficient of the radar multi-channel and the roll error estimate Use the amplitude and phase calibration coefficients to estimate the value Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true rolling error value.

[0084] Specifically, let i=1, where i is the iteration count;

[0085] make Each iteration updates η and Δγ respectively;

[0086] Among them, η is the amplitude and phase calibration coefficient of the radar multi-channel, Δγ is the roll error of the radar multi-channel, is the estimated value of the amplitude and phase calibration coefficients of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0087] The technical solution provided in this embodiment aims to form a second array steering vector matrix by establishing a signal model without channel amplitude and phase errors and only with roll errors. A multivariable optimization problem is constructed based on the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and the first-order Taylor expression of the second array steering vector matrix, and an optimization algorithm based on iterative alternating minimization is used to solve the original problem, thereby eliminating the influence of the roll error during the radar darkroom calibration process. The estimated multi-channel amplitude and phase calibration coefficients are decoupled from the roll error, that is, the calibration coefficient can truly reflect the channel amplitude and phase error. In addition, before calibration, there is no need to use a bubble level to make fine adjustments to the roll error, but only rough adjustments are required, and finally the calibration algorithm automatically compensates.

[0088] Further, in step S1, before driving the servo carrying the radar in the darkroom to rotate, the method includes: placing the radar on the servo in the darkroom, and placing the target angle reflector on the normal line of the far-field position of the radar.

[0089] Furthermore, the multiple azimuth and elevation angles in step S1 are multiple nominal azimuth and elevation angles, which are respectively expressed as: (α1, β1), (α2, β2), …, (α L ,β L );

[0090] The corresponding extracted first array steering vector is expressed as To construct a first array steering vector matrix, the first array steering vector matrix is ​​expressed as:

[0091]

[0092] Among them, A m is the first array steering vector matrix, and L is a positive integer.

[0093] Assume a 4x4 radar square array with 16 array elements and a half-wavelength spacing. Set the roll error Δγ and the amplitude-phase error coefficient η. Measure L = 161 azimuth and elevation steering vectors. First, set the elevation angle to 0 degrees and scan the azimuth angle from -40 degrees to 40 degrees at 1 degree intervals. Then set the azimuth angle to 0 degrees and scan the elevation angle from -40 degrees to 40 degrees at 1 degree intervals. This forms the measurement array flow pattern A. m Let Δγ be 0.5 degrees, and compare the amplitude and phase calibration coefficients estimated by the method of the present invention with those estimated by the traditional method. The amplitude estimation result is as follows: Figure 3A The phase estimation result is shown in Figure 3B As shown in the figure, it can be found that the amplitude and phase results estimated by the method of the embodiment of the present invention are almost the same as the true values, while the error of the traditional method is very large.

[0094] Based on the same inventive concept as the radar channel calibration method in the embodiment of the present invention, the embodiment of the present invention further provides a radar channel calibration device 200, wherein the radar includes at least one transmitting antenna and at least one receiving antenna, and the at least one transmitting antenna and the at least one receiving antenna constitute a plurality of channels, please refer to Figure 4 , the device 200 comprises:

[0095] A driving and echo signal acquisition unit 201 is used to drive the servo carrying the radar in the darkroom to rotate so that the target angle reflector is located at multiple azimuth and elevation angles of the radar, the radar transmits a radar test signal at each azimuth and elevation angle, and for each azimuth and elevation angle, obtains an echo signal fed back by the target angle reflector to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector;

[0096] The signal model building unit 202 is used to build a signal model without channel amplitude and phase errors and with only rolling errors to construct a second array steering vector matrix, and when the rolling error of the radar is lower than a preset value, perform a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including the rolling error;

[0097] An optimization problem constructing unit 203 is used to construct a multivariable optimization problem according to the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and the first-order Taylor expression of the second array steering vector matrix;

[0098] The optimization problem solving unit 204 is used to solve the original problem by using an optimization algorithm based on iterative alternating minimization to obtain the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel.

[0099] Exemplarily, the driving and echo signal acquisition unit 201 extracts the first array steering vector matrix corresponding to the target angle inversion in the following manner:

[0100] Construct multiple azimuth and elevation angles as multiple nominal azimuth and elevation angles, which are expressed as: (α1, β1), (α2, β2),…, (α L ,β L );

[0101] The corresponding extracted first array steering vector is expressed as To construct a first array steering vector matrix, the first array steering vector matrix is ​​expressed as:

[0102]

[0103] Among them, A m is the first array steering vector matrix, and L is a positive integer.

[0104] The first array steering vector matrix is ​​used for subsequent calculation of the rolling error and the amplitude and phase error coefficients of the radar channel.

[0105] Exemplarily, the signal model building unit 202 builds a signal model without channel amplitude and phase errors and only with a roll error in the following manner to construct a second array steering vector matrix, and when the roll error of the radar is lower than a preset value, performs a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression containing a roll error, specifically:

[0106] Using a bubble level, adjusting the roll error of the radar to be lower than a preset value;

[0107] A signal model without channel amplitude and phase errors and only with rolling errors is established, specifically:

[0108] A t = [a1, a2,..., a L ;

[0109] where a l is the l-th array steering vector with roll error but without channel amplitude-phase error, 0 < l ≤ L, and l is a positive integer;

[0110] Perform a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression containing roll error, specifically:

[0111] A t ≈ A i + A′ i Δγ;

[0112] where, A t is the second array steering vector matrix, A i is the ideal array manifold without channel amplitude-phase error and without roll error, A′ i is the derivative of A i with respect to roll error, and Δγ is the roll error of the radar multi-channel.

[0113] Exemplarily, the optimization problem construction unit 203 constructs a multi-variable optimization problem in the following manner, specifically:

[0114] Design the following optimal estimator:

[0115]

[0116] where, A m is the first array steering vector matrix, diag(·) represents forming a diagonal matrix with vectors, η is the amplitude-phase calibration coefficient of the radar multi-channel, and ||·|| F represents the Frobenius norm.

[0117] Exemplarily, the optimization problem solving unit 204 uses an optimization algorithm based on iterative alternating minimization to solve the original problem in the following manner to obtain the estimated value of the amplitude-phase calibration coefficient of the radar multi-channel and the estimated value of the roll error, including:

[0118] By solving the two unknown parameters η and Δγ in the optimal estimator to minimize the result of the optimal estimator, obtain the estimated value of the amplitude-phase calibration coefficient of the radar multi-channel and the estimated value of the roll error Use the estimated value of the amplitude-phase calibration coefficient to approximate the true amplitude-phase calibration coefficient of the radar multi-channel, and use the estimated value of the roll error to approximate the true roll error value.

[0119] Specifically, let i=1, where i is the iteration count;

[0120] make Each iteration updates η and Δγ respectively;

[0121] Among them, η is the amplitude and phase calibration coefficient of the radar multi-channel, Δγ is the roll error of the radar multi-channel, is the estimated value of the amplitude and phase calibration coefficients of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0122] According to another aspect of the present invention, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the radar channel calibration method described in any of the aforementioned embodiments is implemented.

[0123] The specific definition and implementation of the above steps can refer to the steps and methods of the embodiment of the radar channel calibration method, which will not be repeated here. Those of ordinary skill in the art can understand that all or part of the processes in the above embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0124] In summary, although the present invention has been disclosed as above in terms of preferred embodiments, the above preferred embodiments are not intended to limit the present invention. A person skilled in the art may make various changes and modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention shall be based on the scope defined in the claims.

Claims

1. A radar channel calibration method, characterized in that: The radar comprises at least one transmitting antenna and at least one receiving antenna, wherein the at least one transmitting antenna and the at least one receiving antenna form a plurality of channels, and the method comprises: Step S1, driving the servo carrying the radar in the darkroom to rotate so that the target angle reflector is located at multiple azimuth and elevation angles of the radar respectively, the radar transmits a radar test signal at each azimuth and elevation angle respectively, and for each azimuth and elevation angle, obtaining an echo signal fed back by the target angle reflector to the radar test signal and extracting a first array steering vector matrix corresponding to the target angle reflector; Step S2, establishing a signal model without channel amplitude and phase errors and with only roll error to construct a second array steering vector matrix, and when the roll error of the radar is lower than a preset value, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including the roll error; Step S3, constructing a multivariable optimization problem according to the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and the first-order Taylor expression of the second array steering vector matrix; Step S4, using an optimization algorithm based on iterative alternating minimization to solve the original problem, and obtaining the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel.

2. The radar channel calibration method according to claim 1, characterized in that: The sub-steps in step S2 include: Step S21, using a bubble level to adjust the roll error of the radar to be lower than a preset value; Step S22, establishing a signal model without channel amplitude and phase errors and with only rolling errors, specifically: <h2 style=";text-align:left;direction:ltr">A<h2 style=";text-align:left;direction:ltr"> t <h2 style=";text-align:left;direction:ltr"> (a1,a2,...,a)<h2 style=";text-align:left;direction:ltr"> L <h2 style=";text-align:left;direction:ltr"> ]; where a l is the array steering vector of the l-th without channel amplitude-phase error but with roll error, 0 < l ≤ L, and l is a positive integer; Step S23, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including a rolling error, specifically: A t ≈A i +A′ i Δγ; Among them, A t is the second array steering vector matrix, A i is an ideal array flow pattern with no channel amplitude and phase errors and no rolling errors, A′ i A i The derivative of the roll error, Δγ, is the roll error of the radar multi-channel.

3. The radar channel calibration method according to claim 2, characterized in that: In step S3, the sub-steps of the process of constructing a multivariable optimization problem include: Step S31, design the following optimization estimator: Among them, A m is the first array steering vector matrix, diag(·) represents a diagonal matrix formed by vectors, η is the amplitude and phase calibration coefficient of the radar multi-channel, ||·|| F represents the F-norm.

4. The radar channel calibration method according to claim 3, characterized in that: In step S4, an optimization algorithm based on iterative alternating minimization is used to solve the original problem, and the estimated values ​​of the amplitude and phase calibration coefficients and the rolling error of the radar multi-channel are obtained, including: By solving the two unknown parameters η and Δγ in the optimization estimator, the result of the optimization estimator is minimized to obtain the estimated value of the amplitude and phase calibration coefficient of the radar multi-channel and the roll error estimate Use the amplitude and phase calibration coefficients to estimate the value Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true rolling error value.

5. The radar channel calibration method according to claim 4, characterized in that: In step S4, the optimization algorithm based on iterative alternating minimization is used to solve the original problem, and the estimated values ​​of the amplitude and phase calibration coefficients and the rolling error of the radar multi-channel are obtained, which also includes: Let i=1, where i is the iteration count; make Each iteration updates η and Δγ respectively; Among them, η is the amplitude and phase calibration coefficient of the radar multi-channel, Δγ is the roll error of the radar multi-channel, is the estimated value of the amplitude and phase calibration coefficients of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

6. The radar channel calibration method according to claim 1, characterized in that: In step S1, before driving the servo carrying the radar in the darkroom to rotate, the method includes: The radar is placed on a servo in the darkroom and the target angle is placed normal to the far field position of the radar.

7. The radar channel calibration method according to claim 6, characterized in that: The multiple azimuth and elevation angles in step S1 are multiple nominal azimuth and elevation angles, which are respectively expressed as: (α1, β1), (α2, β2), …, (α L ,β L ); The corresponding extracted first array steering vector is expressed as To construct a first array steering vector matrix, the first array steering vector matrix is ​​expressed as: Among them, A m is the first array steering vector matrix, and L is a positive integer.

8. A radar channel calibration device, characterized in that: The radar comprises at least one transmitting antenna and at least one receiving antenna, wherein the at least one transmitting antenna and the at least one receiving antenna form a plurality of channels, and the device comprises: A driving and echo signal acquisition unit, used for driving the servo carrying the radar in the darkroom to rotate, so that the target angle reflector is located at multiple azimuth and elevation angles of the radar, the radar transmits a radar test signal at each azimuth and elevation angle, and for each azimuth and elevation angle, obtains an echo signal fed back by the target angle reflector to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector; a signal model building unit, used for building a signal model without channel amplitude and phase errors and with only rolling error, so as to construct a second array steering vector matrix, and when the rolling error of the radar is lower than a preset value, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression including the rolling error; An optimization problem construction unit, used for constructing a multivariable optimization problem according to the relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and the first-order Taylor expression of the second array steering vector matrix; The optimization problem solving unit is used to solve the original problem by using an optimization algorithm based on iterative alternating minimization to obtain the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the rolling error of the radar multi-channel.

9. A storage medium, characterized in that: The storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the radar channel calibration method according to any one of claims 1 to 7.

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