Radar channel calibration method and apparatus, and storage medium

Abstract

A radar channel calibration method and apparatus, and a storage medium. The method comprises: acquiring an echo signal fed back by a target corner reflector for a radar test signal and extracting a first array steering vector matrix corresponding to the target corner reflector; establishing a signal model having no channel amplitude-phase error and only having a roll error to form a second array steering vector matrix; constructing a multi-variable optimization problem on the basis of the relationship of the first array steering vector matrix, a radar multi-channel amplitude-phase calibration coefficient, and a first-order Taylor expression of the second array steering vector matrix; and using an iteration-based alternating minimization optimization algorithm to solve an original problem.

Description

Radar channel calibration method, device and storage medium

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on June 27, 2023, with application number 202310768846.9 and invention name “Radar channel calibration method, device and storage medium”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of radar technology, and more specifically, to a radar channel calibration method, device, and storage medium. Background Art

[0003] Due to factors such as antenna manufacturing errors, feeder line length errors, and antenna mutual coupling, the radar's multi-channel amplitude and phase inconsistencies can lead to errors in the radar's direction-finding results, or even direction-finding errors. Therefore, to achieve the radar's direction-finding function, amplitude and phase calibration of the radar's multi-channel is required. Technical Solutions

[0004] In a first aspect, an embodiment of the present application provides a radar channel calibration method, wherein the radar includes 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 includes:

[0005] Step S1: driving a servo carrying the radar in a darkroom to rotate so that a 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 in response to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector;

[0006] 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. 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.

[0007] Step S3, constructing 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;

[0008] 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 roll error of the radar multi-channel.

[0009] In some embodiments, the sub-steps in step S2 include:

[0010] Step S21, using a bubble level to adjust the roll error of the radar to be lower than a preset value;

[0011] Step S22, establishing a signal model without channel amplitude-phase error and only with roll error, specifically: A t =[a1,a2,...,a L ;

[0012] 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;

[0013] Step S23, performing a first-order Taylor expansion on the second array steering vector matrix to obtain a first-order Taylor expression containing roll error, specifically: A t ≈A i +A′ i Δγ;

[0014] 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.

[0015] In some embodiments, in step S3, the sub-steps of the process of constructing a multi-variable optimization problem include:

[0016] Step S31, designing the following optimal estimator:

[0017] where, A m is the first array steering vector matrix, diag(·) represents a diagonal matrix formed by vectors, η is the amplitude-phase calibration coefficient of the radar multi-channel, and ||·|| F represents the F norm.

[0018] In some embodiments, in step S4, an optimization algorithm based on iterative alternating minimization is used to solve the original problem, and obtaining the estimated value of the amplitude-phase calibration coefficient and the estimated value of the roll error of the radar multi-channel includes:

[0019] By solving the two unknown parameters η and Δγ in the optimal estimator to minimize the result of the optimal estimator, the estimated value of the amplitude-phase calibration coefficient of the radar multi-channel is obtained and the estimated value of the roll error Using the estimated value of the amplitude-phase calibration coefficient Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true roll error value.

[0020] In some embodiments, in step S4, solving the original problem 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 roll error of the radar multi-channel further includes:

[0021] Let i=1, where i is the iteration count;

[0022] make Each iteration updates η and Δγ respectively;

[0023] Where 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 coefficient of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0024] In some embodiments, in step S1, before driving the servo carrying the radar in the darkroom to rotate, the method includes:

[0025] 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.

[0026] In some embodiments, 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 );

[0027] 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:

[0028] Among them, A m is the first array steering vector matrix, and L is a positive integer.

[0029] In a second aspect, an embodiment of the present application provides a radar channel calibration device, wherein the radar includes 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 multiple channels, and the device includes:

[0030] a driving and echo signal acquisition unit, configured to drive a servo mounted on the radar in the darkroom to rotate so that a target angle reflector is located at a plurality of azimuth and elevation angles of the radar, the radar transmits a radar test signal at each of the azimuth and elevation angles, and, for each of the azimuth and elevation angles, acquire an echo signal fed back by the target angle reflector in response to the radar test signal and extract a first array steering vector matrix corresponding to the target angle reflector;

[0031] a signal model building unit, configured to establish a signal model with no channel amplitude and phase errors and only a roll error, so as to construct a second array steering vector matrix; and, when the roll 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 roll error;

[0032] an optimization problem constructing unit, configured to construct a multivariable optimization problem based on a 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;

[0033] 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.

[0034] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the radar channel calibration method described in any of the above embodiments is implemented.

[0035] Various aspects, features, advantages, etc. of the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. According to the following detailed description in conjunction with the accompanying drawings, the above aspects, features, advantages, etc. of the present invention will become more clear.

[0036] Various aspects, features, advantages, etc. of the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. According to the following detailed description in conjunction with the accompanying drawings, the above aspects, features, advantages, etc. of the present invention will become more clear.

[0037] With reference to the following description and accompanying drawings, specific embodiments of the present invention are disclosed in detail, indicating the manner in which the principles of the present invention can be employed. It should be understood that the embodiments of the present invention are not limited in scope thereby. The embodiments of the present invention encompass numerous variations, modifications, and equivalents within the spirit and scope of the appended claims.

[0038] Features described and / or illustrated with respect to one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments.

[0039] It should be emphasized that the term "include / comprising" when used herein refers to the presence of features, integers, steps or components, but does not exclude the presence or addition of one or more other features, integers, steps or components. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 is a schematic diagram of radar array antenna echo signal reception.

[0042] FIG2 is a flowchart of the steps of a radar channel calibration method provided by an embodiment of the present invention.

[0043] FIG3A is a first schematic diagram of channel phase simulation provided by an embodiment of the present invention.

[0044] FIG3B is a second schematic diagram of channel phase simulation provided by an embodiment of the present invention.

[0045] FIG4 is a schematic structural diagram of a radar channel calibration device provided by an embodiment of the present invention. Modes for Carrying Out the Invention

[0046] In order to facilitate understanding of the various aspects, features and advantages of the technical solution of the present invention, the present invention is described in detail below with reference to the accompanying drawings. It should be understood that the various embodiments described below are only for illustration and are not intended to limit the scope of protection of the present invention.

[0047] In the description of this disclosure, it should be noted that, unless otherwise specified or limited, the term "and / or" herein is merely a description of an association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, and B exists alone. Furthermore, the character " / " herein, unless otherwise specified, generally indicates that the associated objects are in an "or" relationship.

[0048] The technical terms involved in the present invention are described below:

[0049] MIMO (Multiple-Input Multiple-Output) technology uses multiple transmit and receive antennas at the transmitter and receiver, respectively, to transmit signals over multiple channels, thereby improving communication quality. It fully utilizes spatial resources, enabling multiple transmissions and multiple receptions through multiple antennas. This can exponentially increase system channel capacity without increasing spectrum resources or antenna transmit power.

[0050] Figure 1 is a schematic diagram of radar array antenna echo signal reception.

[0051] As shown in Figure 1, 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 length of the feeder 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 calibrated, it will affect the DOA estimation of the target. As mentioned in the background, the radar still has direction-finding errors caused by roll errors.

[0052] Radar amplitude and phase calibration requires a darkroom. By placing angular reflectors at multiple known angles while the radar collects data, the amplitude and phase calibration coefficients for each channel are estimated. During darkroom calibration, the radar must be kept level. A common method is to use a bubble level for fine adjustments. However, if the radar itself is small, even after adjustment with a bubble level, the radar's horizontal plane may still have an error of a few tenths to a few tenths of a degree relative to the standard horizontal plane. This error can be divided into pitch and roll errors. Pitch errors can be reduced using laser illumination combined with mirror reflection, but roll errors are difficult to reduce.

[0053] Because existing bubble-level-based adjustments fail to maintain the radar at a standard horizontal plane, eliminating its roll error is difficult. Consequently, the channel amplitude and phase calibration coefficients obtained with roll error coupled to the roll error fail to truly reflect the channel amplitude and phase errors, resulting in direction-finding errors caused by the roll error in the calibrated radar.

[0054] FIG2 is a flowchart of the steps of a radar channel calibration method provided by an embodiment of the present invention.

[0055] As shown in FIG2 , according to one aspect of the present invention, the radar channel calibration method provided by an embodiment of the present invention includes:

[0056] Step S1: driving a servo carrying the radar in a darkroom to rotate so that a 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 in response to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector;

[0057] 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. 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.

[0058] 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;

[0059] 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 roll error of the radar multi-channel.

[0060] The technical solution disclosed in this invention can be used in single-transmitter, multiple-transmitter, single-receiver radars, and MIMO (Multiple-Input Multiple-Output) radars. MIMO radars, which use multiple-transmitter, multiple-receiver antennas, offer a cost-effective way to improve radar resolution while maintaining a compact antenna footprint. Based on multi-element antennas, MIMO radars use M channels to transmit mutually orthogonal signals. These multiple waveforms remain spatially independent and, after being scattered by the target, are received by N receiving elements. Each element uses M matched filters to match the echoes, resulting in M*N channels of echo data.

[0061] The above steps S1 to S4 are described in detail below.

[0062] 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. The radar transmits a radar test signal at each of the azimuth and elevation angles, and for each of the azimuth and elevation angles, an echo signal fed back by the target angle reflector in response to the radar test signal is obtained, and a first array steering vector matrix corresponding to the target angle reflector is extracted.

[0063] For example, in a MIMO radar system, a pulse sequence is transmitted in a time-division transmission mode. The time required for all array antennas to transmit a pulse signal in turn is a Burst period (i.e., a pulse sequence period). The time of a Burst period is divided into multiple Chirp signal periods, where the multiple Chirp signal periods within a Burst period can be the same or different, and only one antenna transmits a pulse signal in each Chirp signal period.

[0064] 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 represented as (α1, β1), (α2, β2),…, (α L ,β L The radar sends signals at each azimuth and elevation angle, 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 to calculate the roll error and radar channel amplitude and phase error coefficients in the subsequent calculation. Specifically, let A m To measure the array flow pattern.

[0065] 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. 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.

[0066] The sub-steps in step S2 include:

[0067] Step S21, using a bubble level to adjust the roll error of the radar to be lower than a preset value;

[0068] In the embodiment of the present invention, the radar's roll error can be adjusted to a relatively small value by using a bubble level or other methods, for example, a roll error of less than 10 degrees, 2 degrees, or 1 degree. Conversely, if the bubble level is not adjusted properly, the approximate error will be slightly larger.

[0069] Because 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 subjected to Taylor expansion 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 performing the first - order Taylor expansion on the second array steering vector matrix is to convert the expression based on the non - linearity of Δγ into an expression based on the linearity of Δγ, so as to facilitate subsequent compensation and calibration processing.

[0070] Step S22, establish a signal model without channel amplitude - phase error and only with roll error, specifically: A t =[a1,a2,...,a L ;

[0071] 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

[0072] 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: A t ≈A i +A′ i Δγ;

[0073] 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 - channel. A i can be given according to the radar transmission signal wavelength, array geometry structure, and L known azimuth and elevation angles.

[0074] 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 - channel, and the first - order Taylor expression of the second array steering vector matrix.

[0075] In step S3, the sub - steps of the process of constructing the multi - variable optimization problem include:

[0076] Step S31, design the following optimal estimator:

[0077] 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, ||·|| |F represents the F - norm.

[0078] 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 roll error of the radar multi-channel are obtained.

[0079] 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 Estimated values ​​using amplitude and phase calibration coefficients Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true roll error value.

[0080] Specifically, let i=1, where i is the iteration count;

[0081] make Each iteration updates η and Δγ respectively;

[0082] Where 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 coefficient of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0083] The technical solution provided in this embodiment aims to establish a signal model with no channel amplitude and phase errors and only roll errors to form a second array steering vector matrix. 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's multiple channels, and the first-order Taylor expression of the second array steering vector matrix. The original problem is solved using an optimization algorithm based on iterative alternating minimization, thereby eliminating the impact of roll errors during radar darkroom calibration. The estimated multi-channel amplitude and phase calibration coefficients are decoupled from the roll errors, meaning that the calibration coefficients can truly reflect the channel amplitude and phase errors. In addition, before calibration, there is no need to fine-tune the roll error using a bubble level; only rough adjustments are required, and the calibration algorithm automatically compensates for the roll error.

[0084] Furthermore, 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.

[0085] 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 );

[0086] 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:

[0087] Among them, A m is the first array steering vector matrix, and L is a positive integer.

[0088] Assume a 4x4 square radar array with 16 elements and a half-wavelength spacing. Set the roll error Δγ and the amplitude and phase error coefficient η. Measure L = 161 steering vectors at azimuth and elevation angles. 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 Assuming Δγ to be 0.5 degrees, the amplitude and phase calibration coefficients estimated by the method of the present invention are compared with those estimated by the conventional method. The amplitude estimation results are shown in Figure 3A, and the phase estimation results are shown in Figure 3B. As can be seen from the results in the figures, the amplitude and phase estimated by the method of the present invention are almost identical to the true values, while the conventional method has a large error.

[0089] Based on the same inventive concept as the radar channel calibration method in an embodiment of the present invention, an embodiment of the present invention further provides a radar channel calibration device 200. The radar includes at least one transmitting antenna and at least one receiving antenna. The at least one transmitting antenna and the at least one receiving antenna constitute multiple channels. Referring to FIG. 4 , the device 200 includes:

[0090] A driving and echo signal acquisition unit 201 is configured to drive a servo mounted on the radar in the darkroom to rotate so that a target angle reflector is located at a plurality of azimuth and elevation angles of the radar. The radar transmits a radar test signal at each of the azimuth and elevation angles. For each of the azimuth and elevation angles, the radar obtains an echo signal fed back by the target angle reflector in response to the radar test signal and extracts a first array steering vector matrix corresponding to the target angle reflector.

[0091] The signal model building unit 202 is configured to establish a signal model with no channel amplitude and phase errors and only a roll error to construct a second array steering vector matrix, and, when the roll 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 roll error.

[0092] an optimization problem constructing unit 203, configured to construct a multivariable optimization problem based on a relationship between the first array steering vector matrix, the amplitude and phase calibration coefficients of the radar multi-channel, and a first-order Taylor expression of the second array steering vector matrix;

[0093] The optimization problem solving unit 204 is configured to solve the original problem by using an optimization algorithm based on iterative alternating minimization, so as to obtain the estimated values of the amplitude-phase calibration coefficients and the roll error of the radar multi-channel.

[0094] Exemplarily, the driving and echo signal acquisition unit 201 extracts the first array steering vector matrix corresponding to the target corner reflector in the following manner:

[0095] Construct multiple azimuth and elevation angles as multiple nominal azimuth and elevation angles, respectively expressed as: (α1,β1),(α2,β2),…,(α L ,β L );

[0096] The corresponding first array steering vector extracted is expressed as to construct the first array steering vector matrix, and the first array steering vector matrix is expressed as:

[0097] where A m is the first array steering vector matrix, and L is a positive integer.

[0098] The first array steering vector matrix is used for subsequent calculation of the roll error and the radar channel amplitude-phase error coefficient.

[0099] Exemplarily, the signal model establishing unit 202 establishes a signal model without channel amplitude-phase error and only with roll error in the following manner, constructs a second array steering vector matrix, and performs 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, so as to obtain a first-order Taylor expression containing the roll error, specifically:

[0100] Use a bubble level to adjust the roll error of the radar to be lower than the preset value;

[0101] Establish a signal model without channel amplitude-phase error and only with roll error, specifically: A t =[a1,a2,...,a L ;

[0102] where a l is the l-th array steering vector without channel amplitude-phase error and with roll error, 0<l≤L, and l is a positive integer;

[0103] 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: A t ≈A i +A′ i Δγ;

[0104] where At is the second array steering vector matrix, A i is an ideal array flow pattern with no channel amplitude and phase errors and no roll errors, A′ i A i The derivative of the roll error, Δγ, is the roll error of the radar multi-channel.

[0105] Exemplarily, the optimization problem construction unit 203 constructs a multivariable optimization problem in the following manner, specifically:

[0106] Design the following optimal estimator:

[0107] 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.

[0108] Exemplarily, the optimization problem solving unit 204 solves the original problem using an optimization algorithm based on iterative alternating minimization in the following manner to obtain the estimated values ​​of the amplitude and phase calibration coefficients and the estimated value of the roll error of the radar multi-channel, including:

[0109] 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 Estimated values ​​using amplitude and phase calibration coefficients Approximate the amplitude and phase calibration coefficients of the real radar multi-channel, using the roll error estimate Approximate the true roll error value.

[0110] Specifically, let i=1, where i is the iteration count;

[0111] make Each iteration updates η and Δγ respectively;

[0112] Where 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 coefficient of the radar multi-channel, is the estimated value of the radar multi-channel roll error.

[0113] 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.

[0114] 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 skilled in the art will understand that all or part of the processes in the above embodiment methods can be implemented by instructing related hardware through a computer program. 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 may 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 DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0115] In summary, although the present invention has been disclosed above with reference to 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, 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, comprising: 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, wherein: 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, wherein: 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, wherein: 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 Difference Estimate Approximate the true rolling error value.

5. The radar channel calibration method according to claim 4, wherein: 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, wherein: In step S1, before driving the servo carrying the radar in the darkroom to rotate, the following steps are included: 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, wherein: 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, the radar comprising at least one transmitting antenna and at least one receiving antenna, the at least one transmitting antenna and the at least one receiving antenna forming a plurality of channels, comprising: The driving and echo signal acquisition unit is used to drive the servo carrying the radar in the darkroom to rotate. The target angle inverse is located at a plurality of 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, an echo signal fed back by the target angle inverse to the radar test signal is obtained and a first array steering vector matrix corresponding to the target angle inverse is extracted; 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, wherein: 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.

Images