A method and device for generating a combined directional pattern of a MIMO radar transceiver

Abstract

The application provides a MIMO radar transmitting-receiving joint direction pattern generation method and device, and the method comprises the following steps: determining a characteristic vector corresponding to an interference signal by using first echo data obtained during a MIMO radar mute state; determining a corresponding transmitting direction pattern based on the characteristic vector; performing reconstruction processing on a covariance matrix corresponding to second echo data by using the second echo data obtained during a MIMO radar receiving period; determining an optimal loading amount by using the reconstructed covariance matrix; configuring the covariance matrix by using the optimal loading amount based on the reconstructed covariance matrix, so as to determine a receiving direction pattern; and determining a transmitting-receiving joint direction pattern based on the obtained transmitting direction pattern and receiving direction pattern. The application can realize joint design of MIMO radar transmitting-receiving direction patterns, and can effectively improve the target warning detection performance of a radar system under the conditions of fast moving interference and expected signal direction vector error.

Description

Technical Field

[0001] This invention relates to the field of radar target detection technology, and in particular to a method and apparatus for generating MIMO radar transmit and receive patterns. Background Technology

[0002] With the rapid development of jamming technology, more and more jamming sources possess integrated reconnaissance and jamming capabilities, as well as high mobility. By intercepting a series of parameters of the signals emitted by the opponent's radar system, they formulate corresponding jamming measures to affect the opponent's radar system's operational capabilities. This makes the electromagnetic interference environment faced by radar systems increasingly severe. Furthermore, due to uncertainties such as angle estimation errors, antenna element position errors, and mutual coupling effects between antenna elements, the desired signal steering vector error is caused. The main lobe of the adaptive radiation pattern not only fails to align with the correct target signal direction but also causes target signal cancellation, thereby weakening the radar system's early warning and detection performance.

[0003] Existing pattern design methods for MIMO (multiple-in, multiple-out) radar systems typically design the transmit and receive patterns separately, without considering simultaneous design. For fast-moving jamming, current methods counteract it by reducing the sidelobe levels of either the transmit or receive patterns. However, when the jamming power is high, it cannot be completely suppressed, still weakening the radar system's early warning and detection capabilities. Regarding desired signal steering vector errors, most existing methods mitigate their impact on target early warning and detection performance by employing diagonal loading techniques; however, determining the appropriate loading amount is often difficult.

[0004] How to achieve the joint design of the transmit and receive patterns of MIMO radar and effectively reduce the impact of fast-moving interference and the desired signal steering vector error on the target warning and detection performance has always been a focus of relevant researchers. Summary of the Invention

[0005] The technical problem to be solved by the present invention is how to realize the joint design of the transmit and receive patterns of MIMO radar and effectively reduce the impact of fast-moving interference and the desired signal steering vector error on the target warning and detection performance; in view of this, the present invention provides a method and apparatus for generating the joint transmit and receive patterns of MIMO radar.

[0006] The technical solution adopted in this invention is a method for generating a joint MIMO radar transmit and receive pattern, comprising:

[0007] The characteristic vector corresponding to the interference signal is determined by using the first echo data acquired during the MIMO radar's silent state.

[0008] Based on the feature vectors, the corresponding emission pattern is determined;

[0009] The covariance matrix corresponding to the second echo data is reconstructed using the second echo data acquired during the MIMO radar reception period.

[0010] The optimal loading amount is determined using the reconstructed covariance matrix;

[0011] Based on the reconstructed covariance matrix, the covariance matrix is ​​configured using the optimal loading amount to determine the receiving pattern;

[0012] Based on the obtained transmission and reception patterns, a combined transmission and reception pattern is determined.

[0013] In one implementation, determining the feature vector corresponding to the interference signal using the first echo data acquired during radar silence includes:

[0014] The covariance matrix corresponding to the first echo data is determined using the first echo data acquired by the MIMO radar during the silent state.

[0015] Eigenvalue decomposition is performed on the covariance matrix corresponding to the first echo data to determine the eigenvector corresponding to the interference signal.

[0016] In one implementation, determining the corresponding emission pattern based on the feature vector includes:

[0017] Using the criterion of minimizing the sidelobe level of the transmission pattern, an optimization model corresponding to the covariance matrix of the transmission waveform is established using the eigenvectors.

[0018] The optimization model is solved using a convex optimization toolkit to obtain the optimal transmit waveform covariance matrix, thereby obtaining the transmit pattern.

[0019] In one embodiment, the process of reconstructing the covariance matrix corresponding to the second echo data acquired during the MIMO radar reception period includes:

[0020] Eigenvalue matrix is ​​obtained by performing eigenvalue decomposition on the sample covariance matrix corresponding to the second echo data.

[0021] Modify the noise eigenvalues ​​in the eigenvalue matrix;

[0022] The reconstructed covariance matrix is ​​obtained using the modified noise eigenvalues.

[0023] In one implementation, determining the optimal loading amount using the reconstructed covariance matrix includes:

[0024] The reconstructed covariance matrix is ​​diagonally loaded.

[0025] Based on the current covariance matrix, an optimization model is established to minimize the difference between the output signal-to-interference-plus-noise ratio (SINR) and the optimal SINR to determine the optimal loading amount.

[0026] In one implementation, configuring the covariance matrix based on the reconstructed covariance matrix using the optimal loading amount to determine the receiver radiation pattern includes:

[0027] Using the obtained optimal loading amount, determine the optimal loading covariance matrix;

[0028] The adaptive receiving weight vector is determined using the optimal loading covariance matrix.

[0029] The receiving pattern is determined based on the adaptive receiving weight vector.

[0030] In one implementation, determining the joint transmit / receive pattern based on the obtained transmit and receive patterns includes:

[0031] The transmit pattern and the receive pattern are multiplied by a dot product, and the result is used as the combined transmit and receive pattern.

[0032] Another aspect of the present invention provides a MIMO radar transceiver joint pattern generation apparatus, comprising:

[0033] The silent data processing unit is configured to use the first echo data acquired during the silent state of the MIMO radar to determine the feature vector corresponding to the interference signal;

[0034] The emission pattern generation unit is configured to determine the corresponding emission pattern based on the feature vector;

[0035] The reconstruction unit is configured to reconstruct the covariance matrix corresponding to the second echo data using the second echo data acquired during the MIMO radar reception period.

[0036] The optimal loading amount calculation unit is configured to determine the optimal loading amount using the reconstructed covariance matrix;

[0037] The receive pattern generation unit is configured to configure the covariance matrix based on the reconstructed covariance matrix using the optimal loading amount to determine the receive pattern;

[0038] The transmit / receive pattern generation unit is configured to determine the transmit / receive pattern based on the obtained transmit pattern and receive pattern.

[0039] Another aspect of the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the interference detection and automatic avoidance method for unmanned aerial vehicle data links as described in any of the preceding claims.

[0040] Another aspect of the present invention provides a computer storage medium storing a computer program, which, when executed by a processor, implements the steps of the interference detection and automatic avoidance method for unmanned aerial vehicle data links as described in any of the preceding claims.

[0041] By adopting the above technical solution, the present invention can realize the joint design of MIMO radar transmit and receive patterns, and can effectively improve the radar system's early warning and detection performance against targets under conditions of fast-moving interference and desired signal steering vector error. Attached Figure Description

[0042] Figure 1 This is a schematic flowchart of a MIMO radar transmit / receive joint pattern generation method according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic flowchart of another MIMO radar transmit / receive joint pattern generation method according to an embodiment of the present invention;

[0044] Figure 3 This is a structural diagram of a MIMO radar transceiver pattern generation device according to an embodiment of the present invention;

[0045] Figure 4 This is a schematic diagram of an electronic device structure according to an embodiment of the present invention. Detailed Implementation

[0046] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments.

[0047] In the accompanying drawings, the thickness, size, and shape of the objects have been slightly exaggerated for ease of illustration. The drawings are for illustrative purposes only and are not drawn to scale.

[0048] It should also be understood that the terms "comprising," "including," "having," "containing," and / or "comprising," when used in this specification, indicate the presence of the stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or combinations thereof. Furthermore, when expressions such as "at least one of..." appear after a list of listed features, they modify the entire listed feature, not individual elements in the list. Additionally, when describing embodiments of this application, the word "may" is used to mean "one or more embodiments of this application." And the term "exemplary" is intended to refer to an example or illustration.

[0049] As used herein, the terms “basically,” “approximately,” and similar terms are used as terms of approximation rather than terms of degree, and are intended to describe inherent biases in measured or calculated values ​​that will be recognized by those skilled in the art.

[0050] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms (e.g., those defined in common dictionaries) shall be interpreted as having the meaning consistent with their meaning in the context of the relevant art and shall not be interpreted in an idealized or overly formal sense unless expressly so specified herein.

[0051] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0052] The first embodiment of the present invention provides a method for generating a joint MIMO radar transmit and receive pattern, as follows: Figure 1 As shown, it includes the following steps:

[0053] Step S1: Use the first echo data acquired during the MIMO radar silent state to determine the feature vector corresponding to the interference signal;

[0054] Step S2: Determine the corresponding emission pattern based on the feature vectors;

[0055] Step S3: Using the second echo data acquired during the MIMO radar reception period, the covariance matrix corresponding to the second echo data is reconstructed.

[0056] Step S4: Use the reconstructed covariance matrix to determine the optimal loading amount;

[0057] Step S5: Based on the reconstructed covariance matrix, configure the covariance matrix using the optimal loading amount to determine the receiving pattern;

[0058] Step S6: Based on the obtained transmission pattern and the reception pattern, determine the combined transmission and reception pattern.

[0059] For reference Figure 1 or Figure 2 The methods provided in the embodiments will now be described in detail.

[0060] Step S1: Use the first echo data acquired during the MIMO radar silent state to determine the feature vector corresponding to the interference signal;

[0061] In one embodiment, step S1 further includes:

[0062] Step S101: Using the first echo data acquired by the MIMO radar during the silent state, determine the covariance matrix corresponding to the first echo data.

[0063] Specifically, the covariance matrix R can be obtained by using the first echo data received by the MIMO radar during the silent period. J .

[0064]

[0065] Among them, Y J = z(t) + n(t), where z(t) is the interference signal, n(t) is the noise signal, and K is the length of the received echo data.

[0066] Step S102: Perform eigenvalue decomposition on the covariance matrix corresponding to the first echo data to determine the eigenvector corresponding to the interference signal.

[0067] Specifically, we can consider the covariance matrix R. J Perform eigenvalue decomposition to obtain the feature vector u corresponding to the interference signal. q (q = 1, 2, ..., Q).

[0068]

[0069] Among them, U J =[u1,u2,...,u Q ]and These are the eigenvector matrices corresponding to the interference signal and the noise signal, respectively. J =diag([λ1,λ2,...,λ) Q ])and Let N be the eigenvalue matrices corresponding to the interference signal and the noise signal, respectively, where Q is the number of interference signals and N is the number of noise signals. r This represents the number of receiving antenna elements.

[0070] Step S2: Determine the corresponding emission pattern based on the feature vector;

[0071] In one implementation, step S2 further includes:

[0072] Step S201: Using the eigenvectors, an optimization model is established for the covariance matrix of the transmitted waveform, based on the criterion of minimizing the sidelobe level of the transmission pattern.

[0073] Specifically, the derivative constraint method can be used to optimize the design of the emission pattern, and the convex optimization toolkit can be used to solve the problem to obtain the emission pattern.

[0074] For example, an optimization model for the covariance matrix R of the transmitted waveform is established based on the criterion of minimizing the sidelobe level of the transmitted pattern.

[0075]

[0076] sta t (θ s ) H Ra t (θ s )≤tθ s ∈Ω s

[0077] a t (θ1) H Ra t (θ1)=0.5a t (θ0) H Ra t (θ0)

[0078] a t (θ2) H Ra t (θ2)=0.5a t (θ0) H Ra t (θ0)

[0079] N t u q H Ru q ≤ηa t (θ0) H Ra t (θ0)q=1,2,...,Q

[0080] N t (D r u q ) H R(D r u q )≤ηa t(θ0) H Ra t (θ0)q=1,2,...,Q,r=1,2,...,p

[0081]

[0082] R≥0

[0083] Where θ0 is the main lobe pointing towards the center, Ω s The region represents the sidelobe region outside the null point of the first beam, θ1 and θ2 represent the 3dB beamwidth points of the main lobe, η is a pre-set constant used to represent the null depth, D = diag(0,1,...,N-1), c is the radar transmit power, and N... t The number of transmitting antenna elements is r, at(.) represents the transmission steering vector, r = 1, 2, ..., p, and p is the highest order of the derivative constraint.

[0084] Step S202: Solve the optimization model using a convex optimization toolkit to obtain the optimal transmission waveform covariance matrix, thereby obtaining the transmission pattern.

[0085] Specifically, the optimal transmit waveform covariance matrix R can be obtained by using a convex optimization toolkit. o And further obtained the launch pattern P t (θ).

[0086] P t (θ)=a t H (θ)R o a t (θ)

[0087] Where θ is the scanning angle.

[0088] Step S3: Using the second echo data acquired during the MIMO radar reception period, the covariance matrix corresponding to the second echo data is reconstructed.

[0089] In one implementation, step S3 further includes:

[0090] Step S301: Perform eigenvalue decomposition on the sample covariance matrix corresponding to the second echo data to obtain the eigenvalue matrix;

[0091] Specifically, the sample covariance matrix corresponding to the second echo data can be analyzed. Perform feature decomposition.

[0092]

[0093] Where x is the received sample signal, C is the length of the received sample signal, and Us =[u1,u2,...,u Q+1 ] and U nn =[u Q+2 ,u Q+3 ,...,u Nr ] are the eigenvector matrices corresponding to signal interference and noise, respectively. s =diag([λ1,λ2,...,λ) Q+1 ]) and Λ nn =diag([λ Q+2 ,λ Q+3 ,...,λ Nr ]) are the eigenvalue matrices corresponding to signal interference and noise, respectively.

[0094] Step S302: Modify the noise eigenvalues ​​in the eigenvalue matrix;

[0095] Specifically, the noise characteristic values ​​can be modified in the manner provided by the following formula:

[0096]

[0097] in,

[0098] Step S303: Using the modified noise eigenvalues, obtain the reconstructed covariance matrix.

[0099] Specifically, the reconstructed covariance matrix is ​​obtained using the modified noise eigenvalues, as shown in the following equation:

[0100]

[0101] in,

[0102] Step S4: Use the reconstructed covariance matrix to determine the optimal loading amount;

[0103] In one implementation, step S4 further includes:

[0104] Step S401: Diagonal loading is performed on the reconstructed covariance matrix;

[0105] Specifically, the reconstructed covariance matrix is ​​diagonally loaded to obtain the loaded covariance matrix R. l .

[0106]

[0107] Where ρ is the loading amount and I is the identity matrix.

[0108] Step S402: Based on the current covariance matrix, determine the optimal loading amount by establishing an optimization model that minimizes the difference between the output signal-to-interference-plus-noise ratio and the optimal output signal-to-interference-plus-noise ratio.

[0109] Specifically, the optimal loading amount is determined by establishing an optimization model that minimizes the difference between the output signal-to-interference-plus-noise ratio (SINR) and the optimal SINR.

[0110]

[0111] in, For the optimal output signal-to-interference-plus-noise ratio, ξ SINR To output the signal-to-interference-plus-noise ratio.

[0112] Solving the above equation yields the optimal loading amount ρ. opt .

[0113]

[0114] Where α is the scattering coefficient of the target.

[0115] Step S5: Based on the reconstructed covariance matrix, configure the covariance matrix using the optimal loading amount to determine the receiving pattern;

[0116] In one implementation, step S5 further includes:

[0117] Step S501: Using the obtained optimal loading amount, determine the optimal loading covariance matrix;

[0118] Specifically, the optimal loading covariance matrix is ​​obtained using the obtained optimal loading amount, as shown in the following formula.

[0119]

[0120] Step S502: Determine the adaptive receiving weight vector using the optimal loading covariance matrix;

[0121] Specifically, as shown in the following equation, the optimal loading covariance matrix is ​​used. Obtain the adaptive reception weight vector W1.

[0122]

[0123] in, The assumed desired signal reception steering vector.

[0124] Step S503: Determine the receiving pattern based on the adaptive receiving weight vector.

[0125] Specifically, the receiver pattern P is obtained using the adaptive receiver weight vector W1, as shown in the following equation. r(θ).

[0126] P r (θ)=W1 H a r (θ)

[0127] Among them, a r (.) indicates the receiving guide vector.

[0128] Step S6: Based on the obtained transmission pattern and reception pattern, determine the combined transmission and reception pattern.

[0129] In one implementation, step S6 specifically includes:

[0130] The transmit pattern and the receive pattern are multiplied by a dot product, and the result is used as the combined transmit and receive pattern P(θ).

[0131] P(θ=P t (θ)*P r (θ)

[0132] Here, * represents dot product.

[0133] Compared with the prior art, this embodiment has at least the following advantages:

[0134] 1) This embodiment can realize the joint design of MIMO radar transmit and receive patterns;

[0135] 2) This embodiment can effectively improve the radar system's early warning and detection performance against targets under conditions of fast-moving interference and desired signal steering vector error.

[0136] The second embodiment of the present invention, corresponding to the first embodiment, introduces a MIMO radar transceiver joint pattern generation device, such as... Figure 3 As shown, it includes the following components:

[0137] The silent data processing unit is configured to use the first echo data acquired during the silent state of the MIMO radar to determine the feature vector corresponding to the interference signal;

[0138] The emission pattern generation unit is configured to determine the corresponding emission pattern based on the feature vector;

[0139] The reconstruction unit is configured to reconstruct the covariance matrix corresponding to the second echo data using the second echo data acquired during the MIMO radar reception period.

[0140] The optimal loading amount calculation unit is configured to determine the optimal loading amount using the reconstructed covariance matrix;

[0141] The receive pattern generation unit is configured to configure the covariance matrix based on the reconstructed covariance matrix using the optimal loading amount to determine the receive pattern;

[0142] The transmit / receive pattern generation unit is configured to determine the transmit / receive pattern based on the obtained transmit pattern and receive pattern.

[0143] In this embodiment, the silent data processing unit is further configured as follows:

[0144] The covariance matrix corresponding to the first echo data is determined using the first echo data acquired by the MIMO radar during the silent state.

[0145] The covariance matrix corresponding to the first echo data is subjected to eigenvalue decomposition to determine the eigenvector corresponding to the interference signal.

[0146] In this embodiment, the transmission pattern generation unit is further configured as follows:

[0147] Using the criterion of minimizing the sidelobe level of the transmission pattern, an optimization model corresponding to the covariance matrix of the transmission waveform is established using the eigenvectors.

[0148] The optimization model is solved using a convex optimization toolkit to obtain the optimal transmit waveform covariance matrix, thereby obtaining the transmit pattern.

[0149] In this embodiment, the reconstruction unit is further configured as follows:

[0150] Eigenvalue matrix is ​​obtained by performing eigenvalue decomposition on the sample covariance matrix corresponding to the second echo data.

[0151] Modify the noise eigenvalues ​​in the eigenvalue matrix;

[0152] The reconstructed covariance matrix is ​​obtained using the modified noise eigenvalues.

[0153] In this embodiment, the optimal loading amount calculation unit is further configured as follows:

[0154] The reconstructed covariance matrix is ​​diagonally loaded.

[0155] Based on the current covariance matrix, an optimization model is established to minimize the difference between the output signal-to-interference-plus-noise ratio (SINR) and the optimal SINR to determine the optimal loading amount.

[0156] In this embodiment, the receiving radiation pattern generation unit is further configured as follows:

[0157] Using the obtained optimal loading amount, determine the optimal loading covariance matrix;

[0158] The adaptive receiving weight vector is determined using the optimal loading covariance matrix.

[0159] The receiving pattern is determined based on the adaptive receiving weight vector.

[0160] In this embodiment, the transmit / receive joint pattern generation unit is further configured as follows:

[0161] The transmit pattern and the receive pattern are multiplied by a dot product, and the result is used as the combined transmit and receive pattern.

[0162] A third embodiment of the present invention provides an electronic device, such as... Figure 4 As shown, it can be understood as a physical device, including a processor and a memory storing processor-executable instructions. When the instructions are executed by the processor, the following operations are performed:

[0163] Step S1: Use the first echo data acquired during the MIMO radar silent state to determine the feature vector corresponding to the interference signal;

[0164] Step S2: Determine the corresponding emission pattern based on the feature vectors;

[0165] Step S3: Using the second echo data acquired during the MIMO radar reception period, the covariance matrix corresponding to the second echo data is reconstructed.

[0166] Step S4: Use the reconstructed covariance matrix to determine the optimal loading amount;

[0167] Step S5: Based on the reconstructed covariance matrix, configure the covariance matrix using the optimal loading amount to determine the receiving pattern;

[0168] Step S6: Based on the obtained transmit and receive patterns, determine the combined transmit and receive pattern.

[0169] In the fourth embodiment of the present invention, the process of the MIMO radar transceiver joint radiation pattern generation method is the same as that of the first, second, or third embodiments. The difference lies in the engineering implementation: this embodiment can be implemented using software plus necessary general-purpose hardware platforms. While hardware implementation is also possible, the former is often a better approach. Based on this understanding, the method of the present invention can be embodied in the form of a computer software product stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including several instructions to cause a device to execute the method described in the embodiments of the present invention.

[0170] Through the description of specific embodiments, a more in-depth and specific understanding should be gained of the technical means and effects adopted by the present invention to achieve the intended purpose. However, the accompanying drawings are only provided for reference and illustration and are not intended to limit the present invention.

Claims

1. A method for generating a joint MIMO radar transmit and receive pattern, characterized in that, include: The characteristic vector corresponding to the interference signal is determined by using the first echo data acquired during the MIMO radar's silent state. Based on the feature vectors, the corresponding emission pattern is determined; The covariance matrix corresponding to the second echo data is reconstructed using the second echo data acquired during the MIMO radar reception period. The optimal loading amount is determined using the reconstructed covariance matrix; Based on the reconstructed covariance matrix, the covariance matrix is ​​configured using the optimal loading amount to determine the receiving pattern; Based on the obtained transmission pattern and reception pattern, a combined transmission and reception pattern is determined; Determining the corresponding emission pattern based on the feature vector includes: Using the criterion of minimizing the sidelobe level of the transmission pattern, an optimization model corresponding to the covariance matrix of the transmission waveform is established using the eigenvectors. The optimization model is solved using a convex optimization toolkit to obtain the optimal transmit waveform covariance matrix, thereby obtaining the transmit pattern. The process of determining the optimal loading amount using the reconstructed covariance matrix includes: The reconstructed covariance matrix is ​​diagonally loaded. Based on the current covariance matrix, an optimization model is established to minimize the difference between the output signal-to-interference-plus-noise ratio (SINR) and the optimal SINR to determine the optimal loading amount.

2. The MIMO radar transmit / receive joint pattern generation method according to claim 1, characterized in that, The determination of the feature vector corresponding to the interference signal using the first echo data acquired during the MIMO radar silent state includes: The covariance matrix corresponding to the first echo data is determined using the first echo data acquired by the MIMO radar during the silent state. Eigenvalue decomposition is performed on the covariance matrix corresponding to the first echo data to determine the eigenvector corresponding to the interference signal.

3. The MIMO radar transmit / receive joint pattern generation method according to claim 1, characterized in that, The process of reconstructing the covariance matrix corresponding to the second echo data obtained during the MIMO radar reception period includes: Eigenvalue matrix is ​​obtained by performing eigenvalue decomposition on the sample covariance matrix corresponding to the second echo data. Modify the noise eigenvalues ​​in the eigenvalue matrix; The reconstructed covariance matrix is ​​obtained using the modified noise eigenvalues.

4. The MIMO radar transmit / receive joint pattern generation method according to claim 1, characterized in that, The method of configuring the covariance matrix based on the reconstructed covariance matrix using the optimal loading amount to determine the receiver radiation pattern includes: Using the obtained optimal loading amount, determine the optimal loading covariance matrix; The adaptive receiving weight vector is determined using the optimal loading covariance matrix. The receiving pattern is determined based on the adaptive receiving weight vector.

5. The MIMO radar transmit / receive joint pattern generation method according to claim 1, characterized in that, The step of determining the joint transmit and receive pattern based on the obtained transmit and receive patterns includes: The transmit pattern and the receive pattern are multiplied by a dot product, and the result is used as the combined transmit and receive pattern.

6. A MIMO radar transceiver joint pattern generation device, characterized in that, include: The silent data processing unit is configured to use the first echo data acquired during the silent state of the MIMO radar to determine the feature vector corresponding to the interference signal; The emission pattern generation unit is configured to determine the corresponding emission pattern based on the feature vector; The reconstruction unit is configured to reconstruct the covariance matrix corresponding to the second echo data using the second echo data acquired during the MIMO radar reception period. The optimal loading amount calculation unit is configured to determine the optimal loading amount using the reconstructed covariance matrix; The receive pattern generation unit is configured to configure the covariance matrix based on the reconstructed covariance matrix using the optimal loading amount to determine the receive pattern; The transmit / receive pattern generation unit is configured to determine the transmit / receive pattern based on the obtained transmit pattern and receive pattern; The transmission pattern generation unit is further configured as follows: Using the criterion of minimizing the sidelobe level of the transmission pattern, an optimization model corresponding to the covariance matrix of the transmission waveform is established using the eigenvectors. The optimization model is solved using a convex optimization toolkit to obtain the optimal transmit waveform covariance matrix, thereby obtaining the transmit pattern. The optimal loading amount calculation unit is further configured as follows: The reconstructed covariance matrix is ​​diagonally loaded. Based on the current covariance matrix, an optimization model is established to minimize the difference between the output signal-to-interference-plus-noise ratio (SINR) and the optimal SINR to determine the optimal loading amount.

7. An electronic device, characterized in that, The electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 5.

8. A computer storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the steps of the MIMO radar transceiver joint pattern generation method as described in any one of claims 1 to 5.

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