A robust waveform optimization method for interference rejection of simultaneous full polarization radar

Abstract

The application discloses a kind of robustness waveform optimization methods of anti-jamming of simultaneous full polarization radar, the method includes: obtaining the prior parameter required for waveform optimization, interference characteristic matrix is constructed;Detect the target impulse response matrix corresponding to the target azimuth angle of target, determine the target impulse response matrix of target echo signal;According to the target impulse response matrix of the target echo signal, calculate initial filter set and calculate initial signal-to-interference-plus-noise ratio;According to the interference characteristic matrix, the initial filter set and the initial signal-to-interference-plus-noise ratio, determine the optimal transmit waveform and the optimal transmit waveform corresponding to several receiving filter sets.The application can realize the improvement of the suppression performance of intermittent sampling retransmission interference signal of full polarization radar, and can be widely applied in radar signal processing technical field.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, and in particular to a robust waveform optimization method for anti-interference of simultaneously fully polarized radar. Background Technology

[0002] Interrupted Sampling Repeater Jamming (ISRJ), a novel coherent jamming technique derived from digital radio frequency memory (RFMemory), cleverly segments and repeats intercepted radar signals. After pulse compression at the radar receiver, it forms a dense string of false targets resembling the target echo, achieving both suppression and deception of the jammer. Due to its fast response speed and simple engineering implementation, ISRJ is often difficult to suppress effectively using traditional methods. Therefore, countermeasures against ISRJ have become a hot research topic in the field of anti-jamming.

[0003] Existing methods for combating intermittent sampling-forwarding interference can be broadly categorized into three types: The first type uses transmitter waveform design, which involves designing sparse Doppler characteristic waveforms or orthogonal linear frequency modulated signals-phase-coded waveforms transmitted by the radar system, and then filtering out the interference signal at the receiver through segmented filtering. The second type uses receiver signal processing, which focuses on receiver design based on the "identification-filtering" approach, extracting the echo signal characteristics (mainly time and frequency domain characteristics) of intermittent sampling-forwarding interference to suppress the interference signal. The third type combines the first two methods, employing an unmatched filtering system and performing joint optimization design of the transmitter and receiver for the radar system. Due to its high degree of freedom and flexible adjustment, this type of method has a more significant suppression effect on intermittent sampling-forwarding interference while reducing lengthy signal processing procedures. However, current transmitter-receiver methods do not fully utilize the polarization domain information of the jammer, and lack consideration of target characteristics in the "signal" aspect of the signal-to-interference-plus-noise ratio (SINR), resulting in insufficient suppression of intermittent sampling-forwarding interference signals. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a robust waveform optimization method for anti-interference of simultaneously fully polarized radar, so as to improve the suppression performance of fully polarized radar against intermittent sampling and forwarding interference signals.

[0005] This invention provides a robust waveform optimization method for anti-jamming of simultaneously fully polarized radar, the method comprising:

[0006] Obtain the prior parameters required for waveform optimization and construct the interference characteristic matrix;

[0007] Detect the target impulse response matrix corresponding to the target azimuth angle, and determine the target impulse response matrix of the target echo signal;

[0008] Based on the target impulse response matrix of the target echo signal, calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio;

[0009] Based on the interference characteristic matrix, the initial filter bank, and the initial signal-to-interference-plus-noise ratio, the optimal transmit waveform and several receiving filter banks corresponding to the optimal transmit waveform are determined.

[0010] Optionally, obtaining the prior parameters required for waveform optimization and constructing the interference characteristic matrix includes:

[0011] Obtain the scattering matrix of the jammer;

[0012] Obtain the interference vectors for the horizontal channel and the vertical channel;

[0013] An interference characteristic matrix is ​​constructed based on the scattering matrix of the jammer, the interference vector of the horizontal channel, and the interference vector of the vertical channel.

[0014] Optionally, the expression for the scattering matrix of the jammer is:

[0015]

[0016] Where G represents the scattering matrix of the jammer, and HH, HV, VH, and VV represent the number of rows and columns of the matrix;

[0017] The interference vectors of the horizontal channel and the vertical channel are used to generate the interference matrix of the horizontal channel and the interference matrix of the vertical channel, wherein the expression of the interference matrix of the horizontal channel is:

[0018] J H =Diag(j H )

[0019] The expression for the interference matrix of the vertical channel is:

[0020] J V =Diag(j V )

[0021] In the formula, j H j represents the interference vector of the horizontal channel. V J represents the interference vector of the vertical channel. H J represents the interference matrix of the generated horizontal channel. V The interference matrix represents the generated vertical channel.

[0022] Optionally, the expression for the interference characteristic matrix is:

[0023]

[0024] in:

[0025]

[0026]

[0027] In the formula,

[0028] in, J represents the interference characteristic matrix before zero-padding, and W represents the interference characteristic matrix before zero-padding. J I represents the zero-padding matrix, O represents the identity matrix, M represents the number of target echo points, N represents the transmitted signal code length, and C represents the complex field.

[0029] Optionally, the target impulse response matrix corresponding to the detected target azimuth angle is used to determine the target impulse response matrix of the target echo signal, and the expression for the target impulse response matrix of the target echo signal is:

[0030]

[0031] Where T(θ) represents the target impulse response matrix of the target echo signal. The target impulse response matrix represents the target azimuth angle, θ∈(0,2π] represents the target azimuth angle, n represents the number of terms in the target impulse response matrix of the target echo signal, HH, HV, VH, VV represent the number of rows and columns of the matrix, Q represents the distance support length of a single target impulse response matrix, M represents the number of target echo points, and N represents the transmitted signal code length.

[0032] Optionally, the step of calculating the initial filter bank and calculating the initial signal-to-interference-plus-noise ratio (SINNR) specifically involves: determining a number of corresponding receiving filter banks using the minimum variance distortionless filter method, and the expression for calculating the initial filter bank is:

[0033]

[0034] The expression for calculating the initial signal-to-interference-plus-noise ratio is as follows:

[0035]

[0036] in,

[0037] In the formula, SINR represents the initial filter bank. (0)T(θ) represents the initial signal-to-interference-plus-noise ratio, s0 represents the initial transmitted waveform determined based on waveform characteristics, and T(θ) represents the initial transmitted waveform. i ) represents the target impulse response matrix of the target echo signal, and s represents the radar transmitted signal. The covariance matrix representing the interference echo, represents the interference characteristic matrix, ‖·‖ represents finding the 2-norm of a vector or matrix, and (·) H This represents the conjugate transpose operation.

[0038] Optionally, determining the optimal transmit waveform and the corresponding plurality of receive filter banks includes:

[0039] The generalized Dinkbach algorithm is used to determine the transmission waveform corresponding to several steps.

[0040] The minimum variance distortionless filter method is used to determine the several receiving filter groups corresponding to the transmitted waveforms in the aforementioned steps.

[0041] The process iterates repeatedly using the generalized Tinkerbach algorithm to determine the corresponding transmit waveform for several steps, and uses the minimum variance distortionless filter method to determine the corresponding receive filter groups for the transmit waveform for several steps, until the first convergence condition is met, thus obtaining the optimal transmit waveform and the corresponding receive filter groups.

[0042] Optionally, determining the transmission waveform corresponding to several steps using the generalized Dinkbach algorithm includes:

[0043] Initialize the numerator and denominator of the objective function.

[0044] in,

[0045] In the formula, f i (s) represents the numerator of the objective function, g i (s) represents the denominator of the objective function, s represents the radar transmitted signal, Re(·) represents the operation of taking the real part, (·) H w represents the conjugate transpose operation. i Represents the receiving filter, T(θ) i ) represents the target impulse response matrix of the target echo signal. represents the additive white Gaussian noise power, and s represents the radar transmitted signal;

[0046] Solve the convex optimization problem based on the numerator and denominator of the initial objective function;

[0047] The process of solving the convex optimization problem is iterated until the second convergence condition is met, and the emission waveforms corresponding to several steps are determined.

[0048] Optionally, the expression for determining the several receiving filter banks corresponding to the transmitted waveforms corresponding to the several steps using the minimum variance distortionless filter method is as follows:

[0049]

[0050]

[0051] In the formula, s represents several receiving filter banks corresponding to several steps of the transmitted waveform. (m) This represents the transmitted waveform corresponding to the aforementioned steps. These represent several receiving filter groups corresponding to the optimal transmit waveform. T(θ) represents the power of additive white Gaussian noise. i The target impulse response matrix represents the target echo signal.

[0052] In the step of reaching the first convergence condition, the expression for the first convergence condition is:

[0053] |SINR (m) -SINR (m-1) |<ζ

[0054] In the formula, ζ represents the preset convergence accuracy.

[0055]

[0056] In the formula, SINR (m) Represents the signal-to-interference-plus-noise ratio, s (m) This represents the transmitted waveform corresponding to the aforementioned steps. T(θ) represents the power of additive white Gaussian noise. i ) represents the target impulse response matrix of the target echo signal, (·) H This represents the conjugate transpose operation.

[0057] This invention also provides a robust waveform optimization device for anti-jamming of simultaneously fully polarized radar, comprising:

[0058] The first module is used to obtain the prior parameters required for waveform optimization and to construct the interference characteristic matrix.

[0059] The second module is used to detect the target impulse response matrix corresponding to the target azimuth angle and determine the target impulse response matrix of the target echo signal.

[0060] The third module is used to calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio based on the target impulse response matrix of the target echo signal.

[0061] The fourth module is used to determine the optimal transmit waveform and several receive filter groups corresponding to the optimal transmit waveform based on the interference characteristic matrix, the initial filter group, and the initial signal-to-interference-plus-noise ratio.

[0062] This invention also provides an electronic device, which includes a processor and a memory; the memory stores a program; the processor executes the program to perform the aforementioned robust waveform optimization method for anti-interference of simultaneously fully polarized radar; the electronic device has the function of carrying and running the business data processing software system provided in this invention, such as a personal computer (PC), mobile phone, smartphone, personal digital assistant (PDA), wearable device, handheld PC (PPC), tablet computer, vehicle terminal, etc.

[0063] This invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the aforementioned robust waveform optimization method for simultaneous full polarization radar against interference.

[0064] This invention also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned robust waveform optimization method for simultaneous fully polarized radar against interference.

[0065] Embodiments of this invention involve reconnaissance and sensing of initial prior parameters; constructing an interference characteristic matrix based on the prior parameters; determining the initial transmitted waveform based on waveform characteristics; determining the initial receiving filter bank using a minimum variance distortionless filter; effectively solving the intra-pulse waveform of the transmitted signal using an iterative generalized Tinkerbach algorithm based on the initial transmitted waveform and the initial receiving filter; furthermore, fixing the intra-pulse waveform of the transmitted signal, effectively solving the filter bank using a minimum variance distortionless filter; repeating the iterative process until a preset convergence condition is met. This invention can improve the suppression performance of fully polarimetric radar against intermittent sampling and forwarding interference signals. Attached Figure Description

[0066] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 Schematic diagram of the working principle of an intermittent sampling and forwarding jammer;

[0068] Figure 2 A flowchart illustrating signal processing for the receiving filter bank;

[0069] Figure 3 This is a flowchart of the generalized Tinkerbach algorithm in an embodiment of the present invention;

[0070] Figure 4 This is a flowchart illustrating the overall algorithm of an embodiment of the present invention. Detailed Implementation

[0071] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0072] Intermittent sampling-forward jamming (ISBN) is characterized by its fast response speed and simple engineering implementation, making it difficult to effectively suppress using traditional methods. Therefore, countermeasures against ISBN have become a hot research topic in the field of anti-jamming. Among existing ISBN countermeasures, one type employs unmatched filtering and joint optimization design of the transmitter and receiver for the radar system. However, current transmitter-receiver methods do not fully utilize the polarization domain information of the jammer, and lack consideration of target characteristics in the signal-to-interference-plus-noise ratio (SINR), resulting in insufficient suppression of ISBN signals.

[0073] To address the problems existing in the prior art, this invention provides a robust waveform optimization method for anti-jamming of simultaneously fully polarimetric radar, comprising:

[0074] S1. Obtain the prior parameters required for waveform optimization and construct the interference characteristic matrix;

[0075] Specifically, prior parameters may include:

[0076] The jammer's scattering matrix, the interference vector of the horizontal channel, and the interference vector of the vertical channel.

[0077] S2. Detect the target impulse response matrix corresponding to the target azimuth angle, and determine the target impulse response matrix of the target echo signal;

[0078] Specifically, the azimuth angle can be determined by the signals from multiple receiving antennas, and the impulse response matrix characterizes the output-input relationship of the system from a time-domain perspective. Assuming the radar transmitted signal is s = [(s...] H,0 ,s V,0 ),...,(sH,M-1 ,s V,M-1 )] T ∈C 2M×1 The target impulse response matrix expression of the target echo signal is:

[0079]

[0080] Where T(θ) represents the target impulse response matrix of the target echo signal. The target impulse response matrix represents the target azimuth angle, θ∈(0,2π] represents the target azimuth angle, n represents the number of terms in the target impulse response matrix of the target echo signal, HH, HV, VH, VV represent the number of rows and columns of the matrix, Q represents the distance support length of a single target impulse response matrix, M represents the number of target echo points, N represents the transmitted signal code length, and C represents the complex field.

[0081] S3. Calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio based on the target impulse response matrix of the target echo signal;

[0082] Specifically, the signal-to-interference-plus-noise ratio (SINR) refers to the ratio of the signal to the sum of interference and noise in the system. The step of calculating the initial filter bank specifically involves determining several corresponding receiving filter banks using the minimum variance distortionless filter method.

[0083] The expression for calculating the initial filter bank is as follows:

[0084]

[0085] The expression for calculating the initial signal-to-interference-plus-noise ratio is as follows:

[0086]

[0087] in,

[0088] In the formula, SINR represents the initial filter bank. (0) T(θ) represents the initial signal-to-interference-plus-noise ratio, s0 represents the initial transmitted waveform determined based on waveform characteristics, and T(θ) represents the initial transmitted waveform. i ) represents the target impulse response matrix of the target echo signal, and s represents the radar transmitted signal. The covariance matrix representing the interference echo, represents the interference characteristic matrix, ‖·‖ represents finding the 2-norm of a vector or matrix, and (·) H This represents the conjugate transpose operation.

[0089] S4. Based on the interference characteristic matrix, the initial filter bank, and the initial signal-to-interference-plus-noise ratio, determine the optimal transmit waveform and several receiving filter banks corresponding to the optimal transmit waveform.

[0090] Specifically, the optimal transmit waveform can be determined by the generalized Tinkerbach algorithm, and the corresponding receiving filter banks can be determined by the minimum variance distortionless filter method.

[0091] Optionally, in some embodiments, step S1 specifically includes the following steps:

[0092] S11. Obtain the scattering matrix of the jammer;

[0093] Specifically, the scattering matrix reflects the scattering characteristics of the target itself. Intermittent sampling forwarding jamming is a novel coherent jamming method that can subject linear frequency modulated pulse compression radar to coherent false target strings. For intermittent sampling forwarding jamming signals, the expression for the jammer's scattering matrix is:

[0094]

[0095] Wherein, G represents the scattering matrix of the jammer, and HH, HV, VH, and VV represent the number of rows and columns of the matrix.

[0096] S12. Obtain the interference vector of the horizontal channel and the interference vector of the vertical channel;

[0097] Specifically, the interference vectors of the horizontal channel and the vertical channel are used to generate the interference matrix of the horizontal channel and the interference matrix of the vertical channel. The interference matrix of the horizontal channel and the interference matrix of the vertical channel can represent the temporal sampling characteristics of intermittent sampling forwarding interference. The expression of the interference matrix of the horizontal channel is as follows:

[0098] J H =Diag(j H )

[0099] The expression for the interference matrix of the vertical channel is:

[0100] J V =Diag(j V )

[0101] The expression for the intermittently sampled and forwarded interference signal in the horizontal channel after being intercepted and forwarded by the jammer is:

[0102] G HH s J,H +G HV s J,V ∈C M×1

[0103] The expression for the intermittently sampled and forwarded jamming signal in the vertical channel after being intercepted and forwarded by the jammer is:

[0104] G VH s J,H +G VV s J,V ∈C M×1

[0105] Among them, s J,H =WJ H s H ∈C M×1

[0106] s J,V =WJ V s V ∈C M×1

[0107]

[0108] In the formula, j H j represents the interference vector of the horizontal channel. V J represents the interference vector of the vertical channel. H J represents the interference matrix of the generated horizontal channel. V The interference matrix s represents the generated vertical channel. J,H The signal relayed by the jammer in the horizontal channel, s J,V The signal relayed by the jammer in the vertical channel, s H The horizontal channel signal transmitted by the radar system, s V denoted by , W represents the vertical channel signal transmitted by the radar system, W represents the echo length of M×1 under the unified broadband radar system by adding MN zeros to the original interference vector, p represents the corresponding row number in the matrix, q represents the corresponding column number in the matrix, and C represents the complex field.

[0109] S13. Construct an interference characteristic matrix based on the scattering matrix of the jammer, the interference vector of the horizontal channel, and the interference vector of the vertical channel;

[0110] Specifically, the expression for the interference characteristic matrix is:

[0111]

[0112] in:

[0113]

[0114]

[0115] In the formula,

[0116] in, J represents the interference characteristic matrix before zero-padding, and W represents the interference characteristic matrix before zero-padding. J I represents the zero-padding matrix, O represents the identity matrix, M represents the number of target echo points, N represents the transmitted signal code length, and C represents the complex field.

[0117] Optionally, in some embodiments, step S4 specifically includes the following steps:

[0118] S41. Using the generalized Dinkbach algorithm, determine the transmission waveform corresponding to several steps;

[0119] Specifically, determining the transmission waveform corresponding to several steps using the generalized Dinkbach algorithm includes:

[0120] Initialize the numerator and denominator of the objective function.

[0121] in,

[0122] In the formula, f i (s) represents the numerator of the objective function, g i (s) represents the denominator of the objective function, Re(·) represents the operation of taking the real part, (·) H w represents the conjugate transpose operation. i Represents the receiving filter, T(θ) i ) represents the target impulse response matrix of the target echo signal. represents the additive white Gaussian noise power, and s represents the radar transmitted signal;

[0123] Based on the numerator and denominator of the initial objective function, the convex optimization problem is solved as follows:

[0124]

[0125]

[0126]

[0127] In the formula, F represents the transmitted waveform sequence after the m-th iteration of the algorithm. λ λ represents the convergence condition value after the m-th iteration. m This represents the coefficient value at the (m+1)th step after the mth iteration;

[0128] The process of iteratively solving the convex optimization problem continues until the second convergence condition is met, determining the emission waveform corresponding to several steps. The second convergence condition is... The emission waveform corresponding to the aforementioned steps is s (m) ,

[0129] in, It represents a number approximately equal to 0.

[0130] S42. Using the minimum variance distortionless filter method, determine the several receiving filter groups corresponding to the transmitted waveforms in the aforementioned steps.

[0131] Specifically, the expressions for the several receiving filter banks corresponding to the transmitted waveforms of the aforementioned steps are as follows:

[0132]

[0133]

[0134] In the formula, s represents several receiving filter banks corresponding to several steps of the transmitted waveform. (m) This represents the transmitted waveform corresponding to the aforementioned steps. These represent several receiving filter groups corresponding to the optimal transmit waveform. T(θ) represents the power of additive white Gaussian noise. i ) represents the target impulse response matrix of the target echo signal.

[0135] S43. Repeatedly iterate the process of determining the corresponding transmit waveform for several steps using the generalized Tinkerbach algorithm and the determination of the corresponding receive filter groups for the transmit waveform for several steps using the minimum variance distortionless filter method until the first convergence condition is met, thereby obtaining the optimal transmit waveform and the corresponding receive filter groups.

[0136] Specifically, in the step of reaching the first convergence condition, the expression for the first convergence condition is:

[0137] |SINR (m) -SINR (m-1) |<ζ

[0138] The optimal transmission waveform expression is:

[0139] s * =s (m)

[0140] In the formula, ζ represents the preset convergence accuracy.

[0141]

[0142] Among them, SINR (m) Represents the signal-to-interference-plus-noise ratio, s* Represents the optimal transmission waveform, s (m) This represents the transmitted waveform corresponding to the aforementioned steps. T(θ) represents the power of additive white Gaussian noise. i ) represents the target impulse response matrix of the target echo signal, (·) H This represents the conjugate transpose operation. This represents several receiving filter groups corresponding to several steps of the transmitted waveform.

[0143] The implementation process of a robust waveform optimization method for anti-jamming of a simultaneously fully polarized radar according to an embodiment of the present invention is described below:

[0144] Step 1: Use jammer parameter detection equipment to detect the jammer's scattering matrix and the interference vectors of the horizontal and vertical channels. Estimate the additive white Gaussian noise power in the environment. To match the transmitted waveform with the target characteristics, a microwave anechoic chamber is needed to measure the target impulse response matrix of this type of target and construct the jamming characteristic matrix. Specifically, the jammer intercepts a segment of the radar transmitted signal and forwards it multiple times, repeating this interception-forwarding process until the pulse ends. Figure 1 As shown: After intercepting the transmitted signal, the jammer performs a slicing operation to obtain segment 1, and then repeats segment 1 twice; similarly, after an interval of one relay cycle, the jammer performs a slicing operation to obtain segment 4, and then repeats it twice; after another interval of one relay cycle, it slices segment 7, and similarly repeats it twice. Where, T... I T represents the slice width for intermittent sampling interference by the jammer. u This indicates the forwarding period during which the jammer performs intermittent sampling jamming, and M represents the number of times the jammer repeats the forwarding.

[0145] Step 2: Initialize the transmitted waveform based on indicators such as fuzzy function characteristics. According to the target impulse response matrix mentioned above, determine several receiving filter groups corresponding to the initial transmitted waveform through the minimum variance distortionless filter method, and then calculate the initial signal-to-interference-plus-noise ratio.

[0146] Step 3: Based on the above initialization of the transmit waveform and the above receive filter bank, the generalized Tinkerbach algorithm (e.g., ...) is used. Figure 3 (As shown), the transmitted waveform is iteratively optimized to determine the optimal transmitted waveform solution after several iterations;

[0147] Step 4: Determine the filter bank for the target impulse response matrix corresponding to several azimuth angles using the minimum variance distortionless filter method;

[0148] Step 5: Repeat steps 3 and 4 above until the convergence condition is met.

[0149] Finally, according to the above steps (such as...) Figure 4 (As shown) the optimal transmit waveform solution and the corresponding receive filter bank are obtained.

[0150] The receiving filter bank performs signal processing, specifically as follows: Figure 2 As shown: The radar echo signal is obtained based on the target echo and the intermittently sampled and relayed interference echo. The specific expression is: r = s T +s J , where s T =T(θ) i )s, In the formula, s T Represents the target echo, s J This represents intermittent sampling and relaying of interference echoes, where r represents the echo signal received by the radar. Let represent the interference characteristic matrix, and s represent the radar transmitted signal. Using an unmatched filter designed based on the target impulse response matrix, the signal-to-interference-plus-noise ratio (SIR) after processing by the unmatched filter is modulo-operated, and the maximum value among the moduli is obtained. Specifically, the modulo operation for the SIR after processing by the k-th unmatched filter is as follows: k = 1, 2, ..., K, T(θ) i ) represents the target impulse response matrix of the target echo signal, w k Represents T(θ) k The unmatched filter is designed, where 's' represents the radar transmitted signal. Represents the power of additive white Gaussian noise. The covariance matrix representing the interference echo is (·). H represents the conjugate transpose operation, and k represents the number of azimuth angles introduced during the robust design of the target azimuth angle θ.

[0151] This invention also provides a robust waveform optimization device for anti-jamming of simultaneously fully polarized radar, comprising:

[0152] The first module is used to obtain the prior parameters required for waveform optimization and to construct the interference characteristic matrix.

[0153] The second module is used to detect the target impulse response matrix corresponding to the target azimuth angle and determine the target impulse response matrix of the target echo signal.

[0154] The third module is used to calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio based on the target impulse response matrix of the target echo signal.

[0155] The fourth module is used to determine the optimal transmit waveform and several receive filter groups corresponding to the optimal transmit waveform based on the interference characteristic matrix, the initial filter group, and the initial signal-to-interference-plus-noise ratio.

[0156] This invention also provides an electronic device, which includes a processor and a memory; the memory stores a program; the processor executes the program to perform the aforementioned robust waveform optimization method for anti-interference of simultaneously fully polarized radar; the electronic device has the function of carrying and running the business data processing software system provided in this invention, such as a personal computer (PC), mobile phone, smartphone, personal digital assistant (PDA), wearable device, handheld PC (PPC), tablet computer, vehicle terminal, etc.

[0157] This invention also provides a computer-readable storage medium storing a program that is executed by a processor to implement the aforementioned robust waveform optimization method for simultaneous full polarization radar against interference.

[0158] This invention also provides a computer program product or computer program that includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned robust waveform optimization method for simultaneous fully polarized radar against interference.

[0159] In summary, the robust waveform optimization method for anti-jamming of a simultaneously fully polarized radar according to embodiments of the present invention has the following advantages:

[0160] 1. This invention determines the target impulse response matrix of the target echo signal based on the target impulse response matrix corresponding to the azimuth angle of the detected target, and can establish a database of target impulse response matrices corresponding to several target azimuth angles, so that the anti-interference robust waveform of the fully polarized radar has azimuth robustness.

[0161] 2. This invention can improve the suppression performance of fully polarized radar against intermittent sampling and forwarding interference signals.

[0162] 3. This invention introduces a robust processing mechanism with several filter banks, which fully considers the impact of target azimuth angle disturbance on the design of anti-interference waveform.

[0163] 4. When designing anti-interference waveforms, this invention considers that the target is an extended target with multiple scattering centers in the distance dimension. The modeling method for extended targets with multiple scattering centers considers both the time-domain and polarization-domain characteristics of the target, and includes accurate modeling of both types of information.

[0164] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is altered and sub-operations described as part of a larger operation are executed independently.

[0165] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the described functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0166] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0167] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0168] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0169] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0170] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0171] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0172] The above is a detailed description of the preferred embodiments of the present invention, but the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A robust waveform optimization method for anti-jamming of simultaneous fully polarimetric radar, characterized in that, include: Obtain the prior parameters required for waveform optimization and construct the interference characteristic matrix; Detect the target impulse response matrix corresponding to the target azimuth angle, and determine the target impulse response matrix of the target echo signal; Based on the target impulse response matrix of the target echo signal, calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio; Based on the interference characteristic matrix, the initial filter bank, and the initial signal-to-interference-plus-noise ratio, determine the optimal transmit waveform and several receive filter banks corresponding to the optimal transmit waveform; The determination of the optimal transmit waveform and the corresponding plurality of receive filter banks includes: The generalized Dinkbach algorithm is used to determine the transmission waveform corresponding to several steps. The minimum variance distortionless filter method is used to determine the several receiving filter groups corresponding to the transmitted waveforms in the aforementioned steps. The process iterates repeatedly using the generalized Tinkerbach algorithm to determine the corresponding transmit waveform for several steps, and uses the minimum variance distortionless filter method to determine the corresponding receive filter groups for the transmit waveform for several steps, until the first convergence condition is met, thus obtaining the optimal transmit waveform and the corresponding receive filter groups.

2. The robust waveform optimization method for anti-interference of a simultaneously fully polarized radar according to claim 1, characterized in that, The process of obtaining the prior parameters required for waveform optimization and constructing the interference characteristic matrix includes: Obtain the scattering matrix of the jammer; Obtain the interference vectors for the horizontal channel and the vertical channel; An interference characteristic matrix is ​​constructed based on the scattering matrix of the jammer, the interference vector of the horizontal channel, and the interference vector of the vertical channel.

3. The robust waveform optimization method for anti-interference of a simultaneous fully polarimetric radar according to claim 2, characterized in that, The expression for the scattering matrix of the jammer is: ； Where G represents the scattering matrix of the jammer. , , , Represents the number of rows and columns of the matrix; The interference vectors of the horizontal channel and the vertical channel are used to generate the interference matrix of the horizontal channel and the interference matrix of the vertical channel, wherein the expression of the interference matrix of the horizontal channel is: ； The expression for the interference matrix of the vertical channel is: ； In the formula, The interference vector representing the horizontal channel, The interference vector representing the vertical channel. The interference matrix representing the generated horizontal channel, The interference matrix represents the generated vertical channel.

4. The robust waveform optimization method for anti-interference of a simultaneous fully polarimetric radar according to claim 2, characterized in that, The expression for the interference characteristic matrix is: ； in: ； ； In the formula, , ; in, Represents the interference characteristic matrix, This represents the interference characteristic matrix before zero-padding. Represents a zero-padding matrix. Represents the identity matrix. This represents a matrix where all elements are 0. Represents the number of target echo points. Represents the code length of the transmitted signal. It represents the complex field.

5. The robust waveform optimization method for anti-interference of a simultaneously fully polarized radar according to claim 1, characterized in that, The target impulse response matrix corresponding to the detected target azimuth angle is used to determine the target impulse response matrix of the target echo signal. The expression for the target impulse response matrix of the target echo signal is as follows: ； in, The target impulse response matrix represents the target echo signal. The target impulse response matrix represents the target azimuth angle. The azimuth angle of the target is represented by , and n represents the number of terms in the target impulse response matrix of the target echo signal. , , , Represents the number of rows and columns of the matrix. The distance support length represents the impulse response matrix of a single target. Represents the target echo point count. This represents the code length of the transmitted signal.

6. The robust waveform optimization method for anti-interference of a simultaneously fully polarized radar according to claim 1, characterized in that, The calculation of the initial filter bank and the initial signal-to-interference-plus-noise ratio (SINNR) are described. Specifically, the step of calculating the initial filter bank involves determining several corresponding receiving filter banks using the minimum variance distortionless filter method. The expression for calculating the initial filter bank is as follows: ； The expression for calculating the initial signal-to-interference-plus-noise ratio is as follows: ； in, ; In the formula, This represents the initial filter bank. This represents the initial signal-to-interference-plus-noise ratio (SIR). This represents the initial transmit waveform determined based on waveform characteristics. The target impulse response matrix represents the target echo signal. Represents radar transmission signal, The covariance matrix representing the interference echo, Represents the interference characteristic matrix. This represents finding the 2-norm of a vector or matrix. This represents the conjugate transpose operation. This represents the power of additive white Gaussian noise.

7. The robust waveform optimization method for anti-interference of a simultaneously fully polarized radar according to claim 1, characterized in that, The determination of the transmission waveform corresponding to several steps using the generalized Dinkbach algorithm includes: Initialize the numerator and denominator of the objective function. in, , ; In the formula, This represents the numerator of the objective function. This represents the denominator of the objective function. Represents radar transmission signal, This represents the operation of taking the real part. This represents the conjugate transpose operation. Represents the receiving filter. The target impulse response matrix represents the target echo signal. Represents the power of additive white Gaussian noise. Represents radar transmission signals; Solve the convex optimization problem based on the numerator and denominator of the initial objective function; The process of solving the convex optimization problem is iterated until the second convergence condition is met, and the emission waveforms corresponding to several steps are determined.

8. The robust waveform optimization method for anti-interference of a simultaneously fully polarized radar according to claim 1, characterized in that, The expression for determining the several receiving filter banks corresponding to the transmitted waveforms in the several steps using the minimum variance distortionless filter method is as follows: ； ； In the formula, This represents a number of receive filter banks corresponding to the transmitted waveforms of several steps. This represents the transmitted waveform corresponding to the aforementioned steps. These represent several receiving filter groups corresponding to the optimal transmit waveform. Represents the power of additive white Gaussian noise. The target impulse response matrix represents the target echo signal; In the step of reaching the first convergence condition, the expression for the first convergence condition is: ； In the formula, The preset convergence accuracy, ； In the formula, Represents the signal-to-interference-to-noise ratio. This represents the transmitted waveform corresponding to the aforementioned steps. Represents the power of additive white Gaussian noise. The target impulse response matrix represents the target echo signal. This represents the conjugate transpose operation.

9. A robust waveform optimization device for simultaneous fully polarized radar to resist interference, characterized in that, include: The first module is used to obtain the prior parameters required for waveform optimization and to construct the interference characteristic matrix. The second module is used to detect the target impulse response matrix corresponding to the target azimuth angle and determine the target impulse response matrix of the target echo signal. The third module is used to calculate the initial filter bank and the initial signal-to-interference-plus-noise ratio based on the target impulse response matrix of the target echo signal. The fourth module is used to determine the optimal transmit waveform and several receive filter groups corresponding to the optimal transmit waveform based on the interference characteristic matrix, the initial filter group, and the initial signal-to-interference-plus-noise ratio. The determination of the optimal transmit waveform and the corresponding plurality of receive filter banks includes: The generalized Dinkbach algorithm is used to determine the transmission waveform corresponding to several steps. The minimum variance distortionless filter method is used to determine the several receiving filter groups corresponding to the transmitted waveforms in the aforementioned steps. The process iterates repeatedly using the generalized Tinkerbach algorithm to determine the corresponding transmit waveform for several steps, and uses the minimum variance distortionless filter method to determine the corresponding receive filter groups for the transmit waveform for several steps, until the first convergence condition is met, thus obtaining the optimal transmit waveform and the corresponding receive filter groups.

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