Radar Anti-Slicing Interference Method Based on Temporal Anonymity and Wiener Filter Recovery

Abstract

This application belongs to the field of radar detection technology, specifically disclosing a radar anti-slicing interference method based on time-domain concealment and Wiener filtering recovery. The method includes: receiving a mixed signal determined based on the radar transmitted signal; determining a state judgment threshold based on the amplitude of the mixed signal; determining the echo state of the mixed signal at each time point based on the state judgment threshold to generate a state sequence; using weighting coefficients to perform weighted cancellation on the upper and lower branch signals to obtain the residual signal; based on the residual signal, using a sliding window method to determine a target range threshold to determine an estimated signal; and reconstructing the signal based on the estimated signal to obtain the recovered signal; determining the average amplitude of all non-zero points in the upper branch signal to determine a shutdown criterion coefficient; if the shutdown criterion coefficient does not exceed a preset energy discrimination threshold, then the recovered signal is used as the anti-interference output signal. This application can improve interference suppression efficiency and reduce costs.

Description

Technical Field

[0001] This application belongs to the field of radar detection technology, and more specifically, relates to a radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery. Background Technology

[0002] In radar countermeasures, jammers, using DRFM (Radio Frequency Interference Mechanism) equipment, can receive, store, analyze, modulate, and then retransmit radar signals. This type of jamming can create deceptive interference such as false targets and sophisticated interference such as noise modulation, covering target echoes in multiple domains including the frequency, time-frequency, and polarization domains, severely impacting radar target detection and tracking. To effectively counter anti-jamming techniques such as parameter agility, jammers often employ a "short-time storage, short-time retransmission" slicing jamming strategy. This involves rapidly sampling and storing the detected radar signal, then quickly modulating and retransmitting it to ensure the jamming signal parameters are aligned with the radar signal in real time. In this case, traditional anti-jamming methods such as frequency domain filtering, time-frequency filtering, and parameter agility become largely ineffective. While radar can suppress sidelobe interference through spatial filtering, spatial anti-jamming methods are ineffective against mainlobe interference scenarios where the target and jamming angles are relatively close. Furthermore, radar operators can employ system-level countermeasures such as networking and sparse array deployment, leveraging resource advantages for jamming countermeasures. However, this requires complex system combinations and is costly.

[0003] Therefore, when radar faces slice-like deception interference that is difficult to distinguish within the main lobe, how to improve the efficiency of interference suppression and reduce costs is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of this application is to improve the efficiency of interference suppression and reduce costs.

[0005] To achieve the above objectives, in a first aspect, this application provides a radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery, comprising: Receive a mixed signal determined based on radar transmitted signals, determine a state determination threshold based on the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, and generate a state sequence. Based on the state sequence, the upper branch signal is determined by time-domain masking of the mixed signal, the lower branch signal is determined by using a preset linear frequency modulated signal, and the upper branch signal and the lower branch signal are weighted and canceled by weighting coefficients to obtain the remaining signal. Based on the remaining signal, the target range gate is determined using the sliding window method, the estimated signal after Wiener filtering is determined based on the target range gate, and the recovered signal is obtained by reconstructing the signal based on the estimated signal. The average amplitude of all non-zero points in the upper branch signal is determined to determine the shutdown criterion coefficient. If the shutdown criterion coefficient does not exceed the preset energy discrimination threshold, the recovered signal is used as the output signal after anti-interference.

[0006] Optionally, it also includes: If the shutdown criterion coefficient exceeds the preset energy discrimination threshold, the updated remaining signal is used as the new upper branch signal. The steps of weighted cancellation, sliding window optimization, signal reconstruction and coefficient calculation are repeated until the shutdown criterion coefficient does not exceed the preset discrimination threshold, and the final output signal is obtained. The updated remaining signal is determined based on the upper branch signal, the estimated signal, the state sequence, and the weighting coefficients.

[0007] Optionally, the method for determining the state determination threshold includes: Determine the first amplitude mean of the mixed signal over the entire observation period; Set the sampling points whose amplitude exceeds the average of the first amplitude to zero; Calculate the second amplitude mean of all non-zero points in the signal after zeroing, and set the second amplitude mean as the state determination threshold value.

[0008] Optionally, the step of determining the echo state of the mixed signal at each time point based on the state determination threshold and generating a state sequence includes: The echo state at the time point in the mixed signal whose amplitude is lower than or equal to the state determination threshold is determined as the echo-dominant state. The echo state at the moment when the amplitude of the mixed signal is higher than the state determination threshold is determined to be the interference-dominated state. The state sequence is set to 1 at the time point of the echo-dominant state and to 0 at the time point of the interference-dominant state.

[0009] Optionally, the method for obtaining the remaining signal includes: The mixed signal is updated based on the state sequence to obtain the echo mixed signal as the upper branch signal of Wiener filtering; A linear frequency modulated signal with the same waveform parameters as the radar transmitted signal is determined, and the lower branch signal of Wiener filtering is constructed based on the linear frequency modulated signal and the state sequence; The lower branch signal is canceled out with the upper branch signal using a weighting coefficient to obtain the remaining signal.

[0010] Optionally, the step of determining the target range gate using a sliding window method based on the remaining signal, determining the estimated signal after Wiener filtering based on the target range gate, and reconstructing the signal based on the estimated signal to obtain the recovered signal includes: The distance gate of the linear frequency modulated signal is transformed by the sliding window method to obtain the average amplitude of the remaining signal corresponding to each distance gate; Compare the mean amplitude of all distance gates, and determine the target distance gate corresponding to the minimum mean amplitude; The estimated signal after Wiener filtering is generated based on the target distance gate, and the recovered signal is obtained by reconstructing the estimated signal.

[0011] Optionally, the radar transmitted signal is any one of a linear frequency modulated signal, a phase-coded signal, or a single-carrier signal.

[0012] Secondly, this application also provides a radar anti-slicing jamming system based on temporal cloning and Wiener filter recovery, comprising: The state sequence generation module is used to receive a mixed signal determined based on the radar transmitted signal, determine a state determination threshold according to the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, generate a state sequence, and perform a time-domain masking operation on the mixed signal based on the state sequence. The weighted cancellation module is used to determine the upper branch signal by performing time-domain masking on the mixed signal based on the state sequence, determine the lower branch signal by using a preset linear frequency modulated signal, and perform weighted cancellation on the upper branch signal and the lower branch signal by using weighting coefficients to obtain the remaining signal. The signal reconstruction module is used to determine the target range gate based on the remaining signal using the sliding window method, determine the estimated signal after Wiener filtering based on the target range gate, and reconstruct the signal based on the estimated signal to obtain the recovered signal. The output module is used to determine the average amplitude of all non-zero points in the upper branch signal to determine the shutdown criterion coefficient. If the shutdown criterion coefficient does not exceed the preset energy discrimination threshold, the recovered signal is used as the output signal after anti-interference.

[0013] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation thereof.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0015] Fifthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0016] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0017] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: (1) This application processes the mixed radar signal in the time domain and utilizes the time domain characteristics of slice interference. Through adaptive threshold generation and state decision, the interference is located and separated directly in the time domain, improving processing efficiency and real-time performance. A closed-loop iterative optimization mechanism is adopted. The optimal matching parameters are automatically found through Wiener filtering cancellation and sliding window search, and the number of iterations is adaptively controlled. Thus, a stable interference suppression effect is achieved with optimal computational resource consumption, thereby improving interference suppression efficiency and reducing costs.

[0018] (2) The interference state judgment of this application is only related to the signal amplitude and not to the signal waveform. Therefore, it can resist various types of interference such as slice copy-and-forward interference and slice noise modulation interference. It has good generalization ability and potential to resist various types of slice interference, which significantly enhances the radar's adaptive anti-interference ability under unknown interference patterns.

[0019] (3) The interference suppression process of this application does not change the amplitude and phase information of the echo signal. After the above processing is performed on the output signals of the sum and difference channels respectively, the angle measurement can be performed normally, thus realizing the integrity of the radar's angle measurement function under strong slice interference environment. Attached Figure Description

[0020] Figure 1 This is one of the flowcharts illustrating the radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery provided in the embodiments of this application; Figure 2 This is the second flowchart of the radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery provided in the embodiments of this application; Figure 3 This is a schematic diagram of the radar anti-slicing interference system based on temporal cloning and Wiener filtering recovery provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0021] 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.

[0022] In this article, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The symbol " / " in this article indicates that the related objects are in an "or" relationship; for example, A / B means A or B.

[0023] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0024] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0025] In the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more, for example, multiple processing units means two or more processing units, multiple elements means two or more elements, etc.

[0026] The embodiments of this application are described below with reference to the accompanying drawings.

[0027] Reference Figure 1 This application provides a radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery, comprising: S101. Receive a mixed signal determined based on radar transmitted signals, determine a state determination threshold according to the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, and generate a state sequence. S102. Based on the state sequence, perform time-domain masking on the mixed signal to determine the upper branch signal, use a preset linear frequency modulated signal to determine the lower branch signal, and use weighting coefficients to perform weighted cancellation on the upper branch signal and the lower branch signal to obtain the remaining signal; S103. Based on the remaining signal, the target range gate is determined using the sliding window method, the estimated signal after Wiener filtering is determined based on the target range gate, and the recovered signal is obtained by reconstructing the signal based on the estimated signal. S104. Determine the average amplitude of all non-zero points in the upper branch signal to determine the shutdown criterion coefficient. If the shutdown criterion coefficient does not exceed the preset energy discrimination threshold, then the recovered signal is used as the output signal after anti-interference.

[0028] If the shutdown criterion coefficient exceeds the preset energy discrimination threshold, the updated remaining signal is used as the new upper branch signal. The steps of weighted cancellation, sliding window optimization, signal reconstruction and coefficient calculation are repeated until the shutdown criterion coefficient does not exceed the preset discrimination threshold, and the final output signal is obtained. The updated remaining signal is determined based on the upper branch signal, the estimated signal, the state sequence, and the weighting coefficients.

[0029] Specifically, in S101, this embodiment first receives the mixed signal detected by the radar system. The mixed signal includes the echo signal and the interference signal, denoted as... The specific formula is as follows: ; in, Indicates the time of each sampling point. Indicates the echo signal. This indicates the time delay of the interference signal relative to the echo signal. To interfere with the modulated signal, In order to be in Interference modulation signal at any time, The calculation process is as follows: ; in, A rectangular envelope pulse train of slice-type interference. It is a pulse-modulated signal. The repetition period of the pulse train. For the number of interference slices, Let the time-domain pulse width be for each rectangular pulse. For interference waveform modulation signal, This is a convolution operation; A time-domain amplitude analysis is performed on the hybrid signal to calculate its amplitude statistics over the entire observation time window, thereby adaptively determining the state decision threshold, denoted as... .

[0030] Based on this threshold, a state decision is made for each sampling point of the mixed signal: points where the signal amplitude is below or equal to the threshold are determined to be echo-dominant, and points where the amplitude is above the threshold are determined to be interference-dominant. Based on this decision, a state sequence consisting of 1s and 0s is generated, where 1 corresponds to the echo-dominant state and 0 corresponds to the interference-dominant state. This state sequence is essentially a time-domain gating function, providing a basis for subsequent time-domain selective processing.

[0031] As shown in the following formula: .

[0032] Secondly, the state sequence generated in the previous step is used as the core control signal, and two parallel signal preprocessing steps are performed to construct a Wiener filter. The state sequence is then applied to the received mixed signal to perform a time-domain masking operation, i.e., based on... A new output signal is obtained. As the upper branch signal of Wiener filtering .

[0033] Specifically, at the moment when the state sequence is 1, the mixed signal is allowed to pass as is; at the moment when the state sequence is 0, the mixed signal is set to zero. The lower branch: The same state sequence is applied to a locally generated linear frequency modulated reference signal that has waveform parameters completely identical to the radar transmitted signal to obtain the lower branch signal, specifically... , For the lower branch signal, The signal is a linear frequency modulated signal with waveform parameters identical to the radar transmitted signal, including slope and pulse width. The initial phase is 0, the amplitude is 1, and the initial distance gate is... .

[0034] Using Wiener filtering theory, the optimal weight coefficients are calculated as shown in the following formula: ; in, This is the inverse of the covariance matrix, which is obtained from the training sample data to the left and right of the distance cell to be detected. This is the data for the distance unit to be detected. After being weighted, the lower branch signal can best match and cancel the residual interference components in the upper branch signal. The weighted lower branch signal is then canceled out with the upper branch signal to output the residual error signal, i.e., the remaining signal.

[0035] Furthermore, the energy of the remaining signal obtained after cancellation is closely related to whether the time delay of the lower branch reference signal accurately matches the real echo. To find the optimal match, a sliding window method is used for parameter search: the starting distance gate of the linear frequency modulated reference signal is systematically changed. For each set distance gate, the cancellation operation in S102 is repeated, and the average amplitude of the corresponding remaining signal is calculated. After traversing all the distance gates to be searched, an amplitude mean sequence is obtained, and the distance gate corresponding to the minimum value is the target distance gate that achieves the best interference cancellation effect. .

[0036] Based on target distance gate The final Wiener-filtered estimated signal is generated. Finally, using this estimated signal and the optimal weights calculated in S102, the time periods in the original mixed signal that are identified as interference-dominant states by the state sequence are replaced and reconstructed to generate a preliminary recovered signal, i.e., the recovered signal, as shown in the following formula: ; in, To restore the signal, For the upper branch signal, It is the identity matrix. To estimate the signal, The above are the optimal weighting coefficients.

[0037] Finally, S104 is used to determine the iterative convergence and output the final result. First, to evaluate the anti-interference effect of the current processing round and determine whether iterative optimization is needed, the shutdown criterion coefficient is calculated. This coefficient is obtained as follows: First, the average amplitude of all non-zero points in the upper branch signal obtained in S102 is calculated to characterize the average energy level of the current reliable echo; then, the minimum average amplitude of the remaining signal obtained during the search process in S103 is compared with the average energy of this echo, and the ratio constitutes the shutdown criterion coefficient, as shown in the following formula: ; in, It is the average amplitude of all non-zero points in the upper branch signal. This represents the minimum average amplitude of the remaining signal.

[0038] This coefficient is compared with a preset energy discrimination threshold. If the coefficient is less than or equal to the discrimination threshold, it indicates that the current cancellation effect has met the requirements and the interference has been effectively suppressed. At this time, the recovered signal obtained in S103 is directly used as the final output signal of this anti-interference processing.

[0039] If the coefficient is greater than the discrimination threshold, it indicates that there is still significant residual interference. In this case, the remaining signal output by S102 is used as the new signal to be processed, replacing the original mixed signal. Update remaining signals: ; The updated remaining signal is used as the main channel signal, i.e., the upper branch signal. .

[0040] The steps of weighted cancellation, sliding window optimization, signal reconstruction, and coefficient calculation are repeatedly executed to form a closed-loop iteration until the shutdown criterion coefficients meet the conditions, at which point the final signal is output, which is the recovered signal after the iterative loop. Rephrased as: ; in, For the first The estimated signal determined after Wiener filtering. Indicates the first The weight values ​​obtained by Wiener filtering.

[0041] Optionally, the method for determining the state determination threshold includes: Determine the first amplitude mean of the mixed signal over the entire observation period; Set the sampling points whose amplitude exceeds the average of the first amplitude to zero; Calculate the second amplitude mean of all non-zero points in the signal after zeroing, and set the second amplitude mean as the state determination threshold value.

[0042] Specifically, a threshold value for determining the received signal status is set. , The setup process is as follows: During the entire time a signal output is detected, the amplitude of all output signals is averaged, and all amplitudes exceeding the average are set to zero to obtain a new output signal. Then, the amplitude of the new output signal is averaged again, and this second average is the threshold value. ; Optionally, the method for obtaining the remaining signal includes: The mixed signal is updated based on the state sequence to obtain the echo mixed signal as the upper branch signal of Wiener filtering; A linear frequency modulated signal with the same waveform parameters as the radar transmitted signal is determined, and the lower branch signal of Wiener filtering is constructed based on the linear frequency modulated signal and the state sequence; The lower branch signal is canceled out with the upper branch signal using a weighting coefficient to obtain the remaining signal.

[0043] Specifically, the construction and execution process of the Wiener filter cancellation stage is as follows: First, the state sequence is used as a time-domain gating switch and directly applied to the received mixed signal. For moments marked as 1 in the state sequence, i.e., when the echo dominates, the mixed signal is allowed to be preserved as is; for moments marked as 0, i.e., when the interference dominates, the corresponding sample value of the mixed signal is set to zero.

[0044] The output signal is a mixed echo signal, serving as the upper branch signal in the Wiener filter structure. Its main component is the initially selected echo segments. Furthermore, a linear frequency modulated signal with identical waveform parameters (slope, pulse width) to the radar transmitted signal is generated as a reference. This reference signal is also gated through the aforementioned state sequence to generate a signal that exists only during the echo-dominant period; this signal serves as the lower branch signal. The lower branch signal is multiplied by the weighting coefficient and then subtracted from the upper branch signal to complete adaptive cancellation; the output is the remaining signal.

[0045] Optionally, the step of determining the target range gate using a sliding window method based on the remaining signal, determining the estimated signal after Wiener filtering based on the target range gate, and reconstructing the signal based on the estimated signal to obtain the recovered signal includes: The distance gate of the linear frequency modulated signal is transformed by the sliding window method to obtain the average amplitude of the remaining signal corresponding to each distance gate; Compare the mean amplitude of all distance gates, and determine the target distance gate corresponding to the minimum mean amplitude; The estimated signal after Wiener filtering is generated based on the target distance gate, and the recovered signal is obtained by reconstructing the estimated signal.

[0046] Specifically, this embodiment employs a sliding window method as the parameter search strategy. Within a preset range, the initial range gate of the linear frequency modulated reference signal is changed sequentially. For each candidate range gate, the aforementioned Wiener filtering cancellation step is repeated, and the remaining signal generated after this cancellation is recorded. Subsequently, the amplitude average of the remaining signal over the entire observation time is calculated.

[0047] After iterating through all the range gates to be searched, a sequence is obtained consisting of each range gate and its corresponding mean amplitude of the remaining signal. By comparing all the mean amplitudes in this sequence, the minimum value is found. This minimum value means that under this specific range gate, the residual error energy after cancellation is the smallest, that is, the time delay matching degree between the reference signal and the true echo is the highest. Therefore, the range gate corresponding to this minimum value is determined as the final target range gate.

[0048] A new linear frequency modulated signal is generated based on the target range gate; this signal is the estimated signal obtained after Wiener filtering. Finally, this estimated signal is used to reconstruct the signal in the interference segment, outputting a complete recovered signal.

[0049] The following describes this application in detail with reference to specific implementations: Assume the radar transmits a linear frequency modulated signal with a pulse width of 256. 5 bandwidth Sampling rate 10 Each door is spaced 0.1 units apart. The radar search range gate is 1 to 3096, the target echo starting range gate is 260, the starting phase is pi / 4, the jammer releases slice noise modulation interference, samples and forwards the radar signal, and one sampling and forwarding cycle is completed. Within one cycle, the sampling duration is 2. Forwarding time 2 The forwarded signal is obtained by amplifying and modulating the sampled signal through a product (or convolution) of noise. The invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0050] (1) The mixed signal composed of radar echo signal and interference signal received , for: ; in, Indicates the time of each sampling point. Indicates the echo signal. This indicates the time delay of the interference signal relative to the echo signal. To interfere with the modulated signal, A rectangular envelope pulse train of slice-type interference. It is a pulse-modulated signal. For the number of interference slices, The repetition period of the pulse train, in the embodiment , The time-domain pulse width of each rectangular pulse, in the embodiment... , In the example, the signal is an interference waveform modulation signal. It is a narrowband Gaussian noise signal; (2) Set the threshold value for determining the received signal status , The setting process is as follows: During the entire time that a signal output is detected, the amplitude of all output signals is averaged, and all amplitudes exceeding the average are set to zero to obtain a new output signal. Then, the amplitude of the new output signal is averaged again, and this average is the threshold. ; (3) Based on the amplitude distribution of the output signal, determine the echo state at each time point and obtain the state sequence function corresponding to each time point. , Time indicates The output signal at any given time is an echo. Time indicates The output signal at any given time is interference. for: ; in accordance with A new output signal is obtained. As the upper branch signal of Wiener filtering ; (4) Construct the Wiener filter lower branch signal , The signal has the same waveform parameters as the radar transmitted signal, such as slope and pulse width, with an initial phase of 0, an amplitude of 1, and an initial range gate set to... ; (5) The lower branch is multiplied by the weighting coefficient. This signal cancels out the signal from the upper branch, resulting in the remaining signal: ; (6) Take mean amplitude As a distance gate The output energy criterion is determined using the sliding window method. Transform sequentially from 1 to 3096, and calculate the different values ​​for each. The corresponding , to obtain the sequence Select minimum value Corresponding distance gate As The initial distance gate is used to obtain the estimated signal after Wiener filtering. This allows for the acquisition of new recovery signals. : ; Pick ; (7) Find The average amplitude of all non-zero points Calculate the shutdown criterion coefficients Set an energy discrimination threshold ,like ,but This is the output signal after interference suppression, such as Then The main channel signal, i.e. Repeat steps (4)-(7), at this time, the recovery signal is obtained. It can be restated as: ; in, For the first The estimated signal determined after Wiener filtering. Indicates the first The weight values ​​obtained by Wiener filtering.

[0051] Reference Figure 2 , Figure 2 This is a complete flowchart of the application, including the following steps: The radar receives a mixture of interference and echo signals. Echo and interference status at each sampling point; Time Domain Vanishing; Multi-stage Wiener filter recovery; The output signal pulse is compressed after recovery; Measurement of distance and angle information after pulse compression; Output the target location information.

[0052] Reference Figure 3 This application also provides a radar anti-slicing jamming system based on temporal cloning and Wiener filtering recovery, comprising: The state sequence generation module 310 is used to receive a mixed signal determined based on the radar transmission signal, determine a state determination threshold according to the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, generate a state sequence, and perform a time-domain masking operation on the mixed signal based on the state sequence. The weighted cancellation module 320 is used to perform time-domain masking to determine the upper branch signal of the mixed signal based on the state sequence, determine the lower branch signal using a preset linear frequency modulated signal, and perform weighted cancellation of the upper branch signal and the lower branch signal using weighting coefficients to obtain the remaining signal. The signal reconstruction module 330 is used to determine the target range gate based on the remaining signal using the sliding window method, determine the estimated signal after Wiener filtering based on the target range gate, and reconstruct the signal based on the estimated signal to obtain the recovered signal. The output module 340 is used to determine the average amplitude of all non-zero points in the upper branch signal to determine the shutdown criterion coefficient. If the shutdown criterion coefficient is determined to be less than or equal to a preset energy discrimination threshold, the recovered signal is used as the output signal after anti-interference.

[0053] Optionally, a loop module is also included for: If the shutdown criterion coefficient exceeds the preset energy discrimination threshold, the updated remaining signal is used as the new upper branch signal. The steps of weighted cancellation, sliding window optimization, signal reconstruction and coefficient calculation are repeated until the shutdown criterion coefficient does not exceed the preset discrimination threshold, and the final output signal is obtained. The updated remaining signal is determined based on the upper branch signal, the estimated signal, the state sequence, and the weighting coefficients.

[0054] Optionally, the method for determining the state determination threshold includes: Determine the first amplitude mean of the mixed signal over the entire observation period; Set the sampling points whose amplitude exceeds the average of the first amplitude to zero; Calculate the second amplitude mean of all non-zero points in the signal after zeroing, and set the second amplitude mean as the state determination threshold value.

[0055] Optionally, the step of determining the echo state of the mixed signal at each time point based on the state determination threshold and generating a state sequence includes: The echo state at the time point in the mixed signal whose amplitude is lower than or equal to the state determination threshold is determined as the echo-dominant state. The echo state at the moment when the amplitude of the mixed signal is higher than the state determination threshold is determined to be the interference-dominated state. The state sequence is set to 1 at the time point of the echo-dominant state and to 0 at the time point of the interference-dominant state.

[0056] Optionally, the method for obtaining the remaining signal includes: The mixed signal is updated based on the state sequence to obtain the echo mixed signal as the upper branch signal of Wiener filtering; A linear frequency modulated signal with the same waveform parameters as the radar transmitted signal is determined, and the lower branch signal of Wiener filtering is constructed based on the linear frequency modulated signal and the state sequence; The lower branch signal is canceled out with the upper branch signal using a weighting coefficient to obtain the remaining signal.

[0057] Optionally, the step of determining the target range gate using a sliding window method based on the remaining signal, determining the estimated signal after Wiener filtering based on the target range gate, and reconstructing the signal based on the estimated signal to obtain the recovered signal includes: The distance gate of the linear frequency modulated signal is transformed by the sliding window method to obtain the average amplitude of the remaining signal corresponding to each distance gate; Compare the mean amplitude of all distance gates, and determine the target distance gate corresponding to the minimum mean amplitude; The estimated signal after Wiener filtering is generated based on the target distance gate, and the recovered signal is obtained by reconstructing the estimated signal.

[0058] Optionally, the radar transmitted signal is any one of a linear frequency modulated signal, a phase-coded signal, or a single-carrier signal.

[0059] Reference Figure 4Based on the methods in the above embodiments, this application provides an electronic device that may include: a processor 410, a communications interface 420, a memory 430, and a communication bus 440. The processor 410, communications interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions stored in the memory 430 to execute the methods in the above embodiments.

[0060] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, 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 application.

[0061] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0062] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0063] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0064] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory (RAM), flash memory, read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can reside in an ASIC.

[0065] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted through the computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0066] It is understood that the various numerical designations used in the embodiments of this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application.

[0067] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A radar anti-slicing interference method based on temporal cloning and Wiener filtering recovery, characterized in that, include: Receive a mixed signal determined based on radar transmitted signals, determine a state determination threshold based on the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, and generate a state sequence. Based on the state sequence, the upper branch signal is determined by time-domain masking of the mixed signal, the lower branch signal is determined by using a preset linear frequency modulated signal, and the upper branch signal and the lower branch signal are weighted and canceled by weighting coefficients to obtain the remaining signal. Based on the remaining signal, the target range gate is determined using the sliding window method, the estimated signal after Wiener filtering is determined based on the target range gate, and the recovered signal is obtained by reconstructing the signal based on the estimated signal. The average amplitude of all non-zero points in the upper branch signal is determined to determine the shutdown criterion coefficient. If the shutdown criterion coefficient does not exceed the preset energy discrimination threshold, the recovered signal is used as the output signal after anti-interference.

2. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, Also includes: If the shutdown criterion coefficient exceeds the preset energy discrimination threshold, the updated remaining signal is used as the new upper branch signal. The steps of weighted cancellation, sliding window optimization, signal reconstruction and coefficient calculation are repeated until the shutdown criterion coefficient does not exceed the preset discrimination threshold, and the final output signal is obtained. The updated remaining signal is determined based on the upper branch signal, the estimated signal, the state sequence, and the weighting coefficients.

3. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, The method for determining the state determination threshold includes: Determine the first amplitude mean of the mixed signal over the entire observation period; Set the sampling points whose amplitude exceeds the average of the first amplitude to zero; Calculate the second amplitude mean of all non-zero points in the signal after zeroing, and set the second amplitude mean as the state determination threshold value.

4. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, The process of determining the echo state of the mixed signal at each time point based on the state determination threshold and generating a state sequence includes: The echo state at the time point in the mixed signal whose amplitude is lower than or equal to the state determination threshold is determined as the echo-dominant state. The echo state at the moment when the amplitude of the mixed signal is higher than the state determination threshold is determined to be the interference-dominated state. The state sequence is set to 1 at the time point of the echo-dominant state and to 0 at the time point of the interference-dominant state.

5. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, The method for obtaining the remaining signal includes: The mixed signal is updated based on the state sequence to obtain the echo mixed signal as the upper branch signal of Wiener filtering; A linear frequency modulated signal with the same waveform parameters as the radar transmitted signal is determined, and the lower branch signal of Wiener filtering is constructed based on the linear frequency modulated signal and the state sequence; The lower branch signal is canceled out with the upper branch signal using a weighting coefficient to obtain the remaining signal.

6. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, The process of determining a target range gate using a sliding window method based on the remaining signal, determining a Wiener-filtered estimated signal based on the target range gate, and reconstructing the recovered signal based on the estimated signal includes: The distance gate of the linear frequency modulated signal is transformed by the sliding window method to obtain the average amplitude of the remaining signal corresponding to each distance gate; Compare the mean amplitude of all distance gates, and determine the target distance gate corresponding to the minimum mean amplitude; The estimated signal after Wiener filtering is generated based on the target distance gate, and the recovered signal is obtained by reconstructing the estimated signal.

7. The radar anti-slicing interference method based on temporal concealment and Wiener filtering recovery according to claim 1, characterized in that, The radar transmission signal is any one of a linear frequency modulated signal, a phase-coded signal, or a single-carrier signal.

8. A radar anti-slicing jamming system based on temporal concealment and Wiener filtering recovery, characterized in that, include: The state sequence generation module is used to receive a mixed signal determined based on the radar transmitted signal, determine a state determination threshold according to the amplitude of the mixed signal, determine the echo state of the mixed signal at each time point based on the state determination threshold, generate a state sequence, and perform a time-domain masking operation on the mixed signal based on the state sequence. The weighted cancellation module is used to determine the upper branch signal by performing time-domain masking on the mixed signal based on the state sequence, determine the lower branch signal by using a preset linear frequency modulated signal, and perform weighted cancellation on the upper branch signal and the lower branch signal by using weighting coefficients to obtain the remaining signal. The signal reconstruction module is used to determine the target range gate based on the remaining signal using the sliding window method, determine the estimated signal after Wiener filtering based on the target range gate, and reconstruct the signal based on the estimated signal to obtain the recovered signal. The output module is used to determine the average amplitude of all non-zero points in the upper branch signal to determine the shutdown criterion coefficient. If the shutdown criterion coefficient does not exceed the preset energy discrimination threshold, the recovered signal is used as the output signal after anti-interference.

9. An electronic device, characterized in that, include: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, it causes the processor to perform the method as described in any one of claims 1-7.

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