Anti-interference method of SSFA-MCPC signal combined segmented mismatched filtering

Abstract

The invention relates to an anti-interference method for SSFA-MCPC signal combined segmented mismatched filtering, and the method comprises the steps: designing the waveform of an SSFA-MCPC signal, carrying out the segmented chaotic phase coding of an MCPC signal in a time domain, and introducing frequency random agility in a frequency domain, thereby enhancing the randomness of the signal and the mutual shielding capability between sub-pulses, and achieving the anti-interference performance of the SSFA-MCPC signal. And the difference between the target echo and the ISRJ signal is effectively increased. On the basis, a segmented mismatch filtering method is adopted to process echoes, and interference suppression is realized by constructing a sub-pulse matched filter bank, utilizing the pulse pressure peak value difference of interfered and non-interfered sub-pulses and combining an Otsu algorithm to adaptively identify and reject the interfered sub-pulses and reconstructing matched filters. According to the method, three typical ISRJ patterns can be effectively suppressed, interference parameter prior is not needed, the calculation complexity is low, an effective solution is provided for radar interference resistance, and the method has good engineering application prospects.

Description

Technical Field

[0001] This invention belongs to the field of anti-interference technology and relates to an anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals. Background Technology

[0002] With the development of countermeasures technologies, especially the widespread application of Digital Radio Frequency Memory (DFRM) technology, traditional radar systems face a variety of new jamming threats. Repeater jamming, due to its flexible implementation and low dependence on radar parameters, has become a major threat method. Among them, Interrupted Sampling Repeater Jamming (ISRJ), a typical DFRM-based intra-pulse coherent deception jamming, intercepts, delays, and repeats the radar's transmitted signal, obtaining partial pulse compression gain at the radar receiver to form dense false targets. It possesses both deception and suppression jamming effects, with flexible and varied patterns, stronger jamming effectiveness, and severely reduces the radar's target detection and tracking performance.

[0003] Conventional radar anti-jamming methods, such as inter-pulse frequency agility and inter-pulse radio frequency masking, are not effective in suppressing ISRJ. Furthermore, when interference enters from the main lobe of the radar beam, traditional airspace anti-jamming techniques such as sidelobe cancellation and sidelobe concealment also become ineffective. Therefore, effective jamming countermeasures are urgently needed to suppress ISRJ. Currently, there is considerable research on ISRJ countermeasures, broadly categorized into two types: waveform design at the transmitter and signal processing at the receiver. The first type of waveform design method, also known as active anti-jamming strategy, mainly focuses on both transmitter waveform design and joint transmitter-receiver waveform design. The second type of signal processing method, also known as passive anti-jamming strategy, primarily achieves interference suppression through interference reconstruction cancellation or time-frequency analysis filtering. Both of these methods can effectively counter ISRJ, but they also have some drawbacks. For example, they suffer from high computational complexity, poor real-time performance, or the effectiveness of ISRJ countermeasures depends on accurate estimation of interference-related parameters. Furthermore, in existing anti-interrupted sampling-forward (ISRJ) techniques, radar signal waveforms mostly use linear frequency modulation (LFM) signals and their variations, while research on anti-ISRJ for multi-carrier phase-coded (MCPC) signals is relatively limited. Compared to LFM signals, MCPC signals have been verified to achieve a more balanced effect in terms of ambiguity function main-sidelobe ratio, envelope fluctuation control, and spectral efficiency, exhibiting stronger low-interception (LIFO) performance and anti-jamming capabilities. However, current research on MCPC signal anti-ISRJ mainly focuses on waveform design, with limited research on other aspects of MCPC signal anti-ISRJ. Summary of the Invention

[0004] To address the problems existing in the above-mentioned traditional methods, this invention proposes an anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals, which can effectively combat three typical ISRJ patterns without the need for prior interference parameters.

[0005] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions: On the one hand, an anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals is provided, including the following steps: The total echo signal received from the radar is converted into a baseband echo signal by a mixer.

[0006] Based on the multi-carrier phase-coded signal, sub-pulse random frequency agility technology is introduced to design the SSFA-MCPC signal waveform and transmit it.

[0007] The transmitted SSFA-MCPC signal is segmented by time delay to form... P Each sub-pulse signal, constructing P Sub-pulse narrowband matched filter.

[0008] The baseband echo signal is passed through P Each sub-pulse narrowband matched filter performs sub-pulse segmentation pulse compression in parallel to obtain... P Subpulse compression results corresponding to the subpulse narrowband matched filter.

[0009] Based on the peak characteristics of all sub-pulse compression results, the Otsu algorithm is used to adaptively identify the interfered sampled sub-pulses, remove the matched filters of the interfered sampled sub-pulses, and reconstruct the interference mismatch filter.

[0010] Interference suppression is achieved by pulse compression processing of the reconstructed interference mismatch filter and the total echo signal received by the radar.

[0011] One of the above technical solutions has the following advantages and beneficial effects: The aforementioned anti-jamming method for joint segmented mismatch filtering of SSFA-MCPC signals involves designing the SSFA-MCPC signal waveform, performing segmented chaotic phase encoding on the MCPC signal in the time domain, and introducing frequency random agility in the frequency domain. This enhances the randomness of the signal and the mutual masking capability between sub-pulses, effectively increasing the difference between the target echo and the ISRJ signal. Based on this, a segmented mismatch filtering method is used to process the echo. By constructing a sub-pulse matched filter bank, the difference in pulse compression peak values ​​between interfered and uninterrupted sub-pulses is utilized, combined with the Otsu algorithm to adaptively identify and eliminate interfered sub-pulses, and the matched filter is reconstructed to achieve interference suppression. This method can effectively suppress three typical ISRJ patterns, requires no prior interference parameters, has low computational complexity, and provides an effective solution for radar anti-jamming, showing good engineering application prospects. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or the conventional technology, the drawings used in the description of the embodiments or the conventional technology will be briefly introduced below. Obviously, the 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.

[0013] Figure 1 This is a schematic diagram of the ISRJ principle; Figure 2 This is a flowchart illustrating an anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals in one embodiment; Figure 3 Here is a flowchart of the joint segmented mismatch filtering anti-interference process for SSFA-MCPC signals in one embodiment; Figure 4 This is a time-frequency structure diagram of the SSFA-MCPC signal in one embodiment; Figure 5 Here is a three-dimensional blurred image of the SSFA-MCPC signal in one embodiment; Figure 6 This is a pulse pressure effect diagram before and after ISDRJ interference suppression in one embodiment, where... Figure 6 (a) shows the effect of ISDRJ interference on pulse pressure before suppression. Figure 6 (b) shows the pulse pressure effect after ISDRJ interference suppression; Figure 7 This is a pulse pressure effect diagram before and after ISPRJ interference suppression in one embodiment, where... Figure 7 (a) shows the effect of ISPRJ interference on pulse pressure before suppression. Figure 7 (b) shows the pulse pressure effect after ISPRJ interference suppression; Figure 8 This is a pulse pressure effect diagram before and after ISCRJ interference suppression in one embodiment, where... Figure 8 (a) shows the effect of ISCRJ interference suppression on pulse pressure. Figure 8 (b) Pulse pressure effect after ISCRJ interference suppression; Figure 9 This is a schematic diagram illustrating the variation of SJRIF of ISDRJ, ISPRJ, and ISCRJ with SNR under different JSR conditions in one embodiment. Figure 9 (a) is a schematic diagram showing the variation of ISDRJ's SJRIF with SNR under different JSR conditions. Figure 9 (b) is a schematic diagram showing the variation of ISPRJ's SJRIF with SNR under different JSR conditions. Figure 9 (c) is a schematic diagram showing the variation of ISCRJ's SJRIF with SNR under different JSR conditions; Figure 10 For one embodiment, a performance evaluation of different signals is provided, wherein Figure 10 (a) shows the relationship between SJRIF and SNRs under the condition of JSR=6dB. Figure 10 Figure (b) shows the relationship between SJRIF and SNRs under the condition of JSR=9dB. Figure 10 (c) shows the relationship between SJRIF and SNRs under the condition of JSR=12dB. Figure 10 (d) is the curve showing the relationship between SJRIF and SNRs under the condition of JSR=15dB; Figure 11 This is a performance comparison of different methods in one embodiment, wherein Figure 11 (a) shows the variation curve of SJRIF under ISDRJ with different JSRs. Figure 11 (b) shows the curves of SJRIF under ISPRJ with different JSRs. Figure 11 (c) is a graph showing the variation of SJRIF under ISCRJ with different JSRs. Detailed Implementation

[0014] 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.

[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0016] It should be noted that, in this document, the reference to "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The presentation of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art will understand that the embodiments described herein can be combined with other embodiments. The term "and / or" as used herein refers to any combination of one or more of the associated listed items, and all possible combinations, including such combinations.

[0017] The embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0018] Interrupted Sampling Repeater Jamming (ISRJ) uses a Digital Radio Frequency Memory (DFRM) jammer to undersample and rapidly repeat intercepted radar signals, generating multiple sub-signals coherent with the radar signal. By cleverly utilizing the matched filtering characteristics of pulse compression radar, a series of false targets can be created at the radar receiver in a short time. Since the repeating jamming signals are coherent with the radar's transmitted signal, high signal processing gain can be achieved after pulse compression, thus achieving deception and suppression jamming effects. ISRJ is generally classified into Interrupted Sampling Direct Repeater Jamming (ISDRJ), Interrupted Sampling Periodic Repeater Jamming (ISPRJ), and Interrupted Sampling Cyclic Repeater Jamming (ISCRJ) based on the jammer's repeating pattern. Different repeating methods produce different jamming effects and correspond to different jammer operating modes. The working principle of ISRJ is as follows: Figure 1 As shown.

[0019] ISDRJ immediately forwards the current segment immediately after sampling the signal in each sampling period, which can be represented as: (1) in, The expression for intermittent sampling and direct forwarding of interference signals is given. The expression for the radar transmitted signal. The jammer performs synchronous sampling with a pulse width of 0, and the sampling and forwarding delay is 0. The number of sampling pulses, To interfere with the sampling duration, To interfere with the sampling period.

[0020] ISPRJ repeatedly forwards the current sampled segment after sampling the signal within a sampling period until the start of the next sampling period, at which point it stops forwarding and begins a new round of sampling and forwarding. Number of repeated forwardings. , can be represented as: (2) in, The expression for intermittent sampling and repeated forwarding interference signal is as follows: K This represents the number of times the message is forwarded repeatedly.

[0021] ISCRJ samples and stores the signal within each sampling period. Besides forwarding the sampled segments of the current sampling period, it also forwards all previously stored sampled segments in reverse order. (Number of loop forwardings) , , can be represented as: (3) in, The expression for intermittent sampling and cyclic forwarding interference signal is as follows: R This represents the number of times the message is forwarded in a loop.

[0022] To address the threat of ISRJ interference, a combined active and passive anti-interference strategy is proposed, which integrates SSFA-MCPC signal waveform design with segmented mismatch filtering.

[0023] In one embodiment, such as Figure 2 As shown, an anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals is provided, which may include the following processing steps 1 to 6: Step 1: Convert the total echo signal received from the radar into a baseband echo signal using a mixer.

[0024] Specifically, suppose there is a scattering point target located at a distance of [missing information] from the radar. The total echo signal received by the radar includes: target echo signal, intermittent sampling and forwarding jamming signal, and Gaussian white noise.

[0025] Step 2: Introduce sub-pulse random frequency agility technology on the basis of multi-carrier phase-coded signal, design SSFA-MCPC signal waveform, and transmit it.

[0026] Specifically, from a waveform design perspective, the SSFA-MCPC signal employs a Logistic chaotic sequence with good pseudo-randomness and autocorrelation performance to perform phase-coded modulation on each symbol of the traditional MCPC signal in the time domain. In the frequency domain, it introduces frequency agility to process the MCPC signal, randomly extracting fixed-length code segments from different subcarriers. Through frequency-coded modulation, it achieves random agility in the frequency of each segmented sub-pulse within the pulse, giving the signal anti-ISRJ characteristics, intra-pulse white noise, and low inter-pulse correlation. Due to the discontinuity of ISRJ sampling, the complete time-frequency characteristics of the signal cannot be obtained, increasing the difference between the radar signal and the interference signal. Simultaneously, because the segmented sub-pulses are orthogonal in both the time and frequency domains, they can better mask each other, thus effectively suppressing ISRJ interference.

[0027] Based on the discontinuous and periodic characteristics of ISRJ sampling, intra-pulse frequency agility technology is introduced into MCPC radar signals. SSFA-MCPC signals are designed by incorporating sub-pulse random frequency agility technology on the basis of multi-carrier phase-coded (MCPC) signals. This further enhances the difference between target echoes and interference signals, improves the mutual cover capability between sub-pulses, and effectively overcomes the high peak-to-average power ratio (PAPR) of MCPC signals.

[0028] Step 3: The transmitted SSFA-MCPC signal is segmented by time delay to form... P Each sub-pulse signal, constructing P Sub-pulse narrowband matched filter.

[0029] Specifically, analysis of the intermittent sampling and forwarding interference principle reveals that the interference exhibits discontinuous time-domain sampling, meaning the signal can only be sampled in segments. Therefore, the segmented sub-pulses of the SSFA-MCPC signal designed in this application can mutually mask each other. That is, when the jammer's sampling and signal segmentation are synchronized, segment 2 is not sampled when segment 1 is sampled; this can be understood as segment 1 masking segment 2. Based on this masking and orthogonal waveforms, processing the echo and utilizing the unsampled signal for radar interference suppression and parameter extraction is a feasible approach. Pulse compression is a classic method in radar signal processing, and the flexible structure of the SSFA-MCPC signal allows for diverse pulse compression methods. Unlike traditional matched-filter pulse compression, this paper employs a segmented pulse compression method to identify and sort interference sampling sub-pulses, based on the orthogonal and random variations of the signal sub-pulses in the time-frequency domain.

[0030] Step 4: Pass the baseband echo signal through P Each sub-pulse narrowband matched filter performs sub-pulse segmentation pulse compression in parallel to obtain... P Subpulse compression results corresponding to the subpulse narrowband matched filter.

[0031] Specifically, to address the discontinuous sampling characteristics of ISRJ, a segmented mismatch filtering algorithm is proposed. A sub-pulse matched filter bank is constructed to perform segmented pulse compression processing on the echo. Taking advantage of the higher pulse compression peak value of the interfered sampling sub-pulse, the Otsu algorithm is used to adaptively identify the interfered sub-pulse, and the interference mismatch filter is reconstructed to achieve interference suppression, thereby ensuring the detection of the real target.

[0032] The receiver first constructs a sub-pulse matched filter bank by segmenting the transmitted signal, and performs segmented pulse compression processing on the echo signal. It then uses the difference in pulse compression peak value to calculate the threshold based on the Otsu algorithm to adaptively identify whether each sub-pulse is interfered with and sampled, thereby achieving interference suppression through mismatch filtering.

[0033] Step 5: Based on the peak characteristics of all sub-pulse compression results, the Otsu algorithm is used to adaptively identify the interfered sampled sub-pulses, remove the matched filter of the interfered sampled sub-pulses, and reconstruct the interference mismatch filter.

[0034] Specifically, due to the intermittent sampling and delayed forwarding characteristics of the jammer, only a portion of the transmitted signal's segmented sub-pulses are sampled and forwarded. Therefore, if the signal is divided into multiple sub-pulses, these sub-pulses can be categorized as jammed sampled sub-pulses and unjammed sampled sub-pulses. After sampling a sub-pulse, the jammer forwards it. The echo signal contains not only the target echo but also the sampled sub-pulse segment forwarded by the jammer. The sampled sub-pulse experiences higher coherence processing gain in matched filtering. Furthermore, to achieve deception and suppression, the jamming energy is generally much greater than the target energy. Therefore, after segmented pulse compression, the jammed and unjammed sampled sub-pulses can be distinguished by their pulse compression peak values, with the sampled sub-pulse's peak value being higher than that of the unsampled sub-pulses. Based on this peak value difference, the Otsu algorithm is used to classify and identify whether a sub-pulse has been jammed.

[0035] Otsu is a classic adaptive thresholding segmentation algorithm that automatically calculates the optimal threshold to achieve image segmentation by maximizing the inter-class variance, thus maximizing the separability between the two classes after segmentation. Therefore, this method first calculates the peak value of all sub-pulses after matched filtering, then uses the Otsu algorithm to calculate the optimal threshold of the peak value. The optimal threshold is then used to identify whether the sub-pulse has been sampled with interference, completing the reconstruction of the mismatched filter and achieving interference suppression.

[0036] Step 6: Perform pulse compression processing on the reconstructed interference mismatch filter and the total echo signal received by the radar to achieve interference suppression.

[0037] The aforementioned anti-jamming method for joint segmented mismatch filtering of SSFA-MCPC signals involves designing the SSFA-MCPC signal waveform, performing segmented chaotic phase encoding on the MCPC signal in the time domain, and introducing frequency random agility in the frequency domain. This enhances the randomness of the signal and the mutual masking capability between sub-pulses, effectively increasing the difference between the target echo and the ISRJ signal. Based on this, a segmented mismatch filtering method is used to process the echo. By constructing a sub-pulse matched filter bank, the difference in pulse compression peak values ​​between interfered and uninterrupted sub-pulses is utilized, combined with the Otsu algorithm to adaptively identify and eliminate interfered sub-pulses, and the matched filter is reconstructed to achieve interference suppression. This method can effectively suppress three typical ISRJ patterns, requires no prior interference parameters, has low computational complexity, and provides an effective solution for radar anti-jamming, showing good engineering application prospects.

[0038] In one embodiment, step 2 includes: using a Logistic chaotic sequence to perform phase coding modulation on each symbol of the traditional MCPC signal in the time domain; introducing the concept of frequency agility in the frequency domain to process the MCPC signal, randomly extracting code segments of fixed length on different subcarriers, and realizing random agility of the frequency of each segment subpulse within the pulse through frequency coding modulation, completing the SSFA-MCPC signal waveform design, and transmitting the SSFA-MCPC signal waveform.

[0039] In one embodiment, the complex envelope of the transmitted SSFA-MCPC signal is: (4) in, The complex envelope of the transmitted SSFA-MCPC signal. t For time, It is the number of subcarriers; For the first p Complex weighting factors on each subcarrier, and These represent the frequency-weighted amplitude and the weighted phase, respectively. For the first p Complex envelope of subcarrier signals; For the first p Subcarrier frequencies, For the first p Random frequency coding of each subcarrier, For subcarrier frequency spacing, The duration of a single symbol; It is the number of sub-pulse symbols in each segment; For the first p On the subcarrier m Phase encoding of each chip; It is a rectangular envelope pulse; The duration of each segmented sub-pulse, the signal bandwidth, and the pulse duration are respectively... and .

[0040] Specifically, the time-frequency structure of the SSFA-MCPC signal is as follows: Figure 4 As shown. From Figure 4 It can be seen that, compared with the MCPC signal, the SSFA-MCPC signal adds one-dimensional modulation, giving the signal two-dimensional modulation agility and optimization capabilities, and enhancing the signal's randomness and unpredictability. Due to the flexible variation of sub-pulse frequency and phase coding method, the proposed waveform has excellent low interception performance, while reducing the influence of interference sidelobes, facilitating subsequent anti-interference processing.

[0041] To analyze the anti-interference effect of the signal, starting from the output of the matched filter, the ambiguity function of the SSFA-MCPC signal is calculated as follows: (5) (6) in, , for p=l The case where the fuzzy function is the main part is... for p l In this case, the side lobe is blurred. rectangular envelope pulse The ambiguity function. It can be seen that the ambiguity function of the SSFA-MCPC signal is essentially... The result after translation and modulation, such as Figure 5 As shown.

[0042] from Figure 5 As can be seen, the SSFA-MCPC signal blur map is thumbtack-shaped, with a relatively flat time-frequency distribution and only a single central peak. Compared with the slanted blade-shaped blur function of the LFM signal, the thumbtack-shaped blur function has no distance-Doppler coupling and lower sidelobe characteristics. Therefore, the SSFA-MCPC signal has high measurement accuracy and excellent target detection capability.

[0043] In one embodiment, the total echo signal received by the radar is: (7) The distance of a scattering point target from the radar is R Then the target echo signal can be expressed as: (8) Assume the distance between the jammer and the radar. The intermittent sampling and forwarding interference signal is: (9) in, The total echo signal received by the radar. For the target echo signal, To intermittently sample and forward interference signals, t For time, The amplitude of the echo signal. For the target echo signal complex envelope, For the first k The echo of the radar transmitted signal sampled by the jammer during the second relay. For the target echo delay, Radar for the location and range of the scattering point target. At the speed of light, It is the number of subcarriers. p It is the first p Number of subcarriers; For the first p Subcarrier frequencies, For the first p Complex weighting factors on each subcarrier, For the first p On the subcarrier m Phase encoding of each chip, For a rectangular envelope pulse, The duration of each segmented sub-pulse, The duration of a single symbol; It is the number of sub-pulse symbols in each segment; For the amplitude of the interference signal, To interfere with echo delay, This represents Gaussian white noise. K To interfere with the number of forwards, N To determine the number of interference sampling pulses, To interfere with the sampling period, To interfere with echo delay, This is the duration of the interference sampling.

[0044] In one embodiment, step 3 includes: dividing the transmitted SSFA-MCPC signal into segments based on the sub-pulse width and time delay. P Each segment has random time-domain coding, and its spectrum is randomly distributed across different subcarriers, resulting in... P The time-domain expression of each sub-pulse signal; based on P The time-domain impulse response of each sub-pulse signal as P A sub-pulse narrowband matched filter, resulting in a... P A subpulse narrowband matched filter bank consists of several subpulse narrowband matched filters.

[0045] In one embodiment, the first p The time-domain expression of each segmented sub-pulse signal is: (10) in, For the first p Time-domain expression of segmented sub-pulse signals, The duration of each segmented sub-pulse, The complex envelope of the transmitted SSFA-MCPC signal. It is a rectangular envelope pulse. t For time.

[0046] Specifically, pulse compression is a classic method in radar signal processing, and the flexible structure of the SSFA-MCPC signal allows for diverse pulse compression methods. Unlike traditional matched-filter pulse compression, this paper employs a segmented pulse compression method to classify and determine interference sampling sub-pulses, taking into account the dual modulation characteristics of radar transmitted signals—frequency agility and phase coding within the pulse—where each sub-pulse is orthogonal and randomly changing in the time-frequency domain. The time delay is divided according to the sub-pulse width. P The segments are randomly encoded in the time domain and their spectra are randomly distributed on different subcarriers, resulting in the first segment as shown in formula (10). p The time-domain expression of a segmented sub-pulse signal.

[0047] Then the first p Time-domain impulse response of a sub-pulse matched filter This is equivalent to dividing the original single broadband matched filter into... P Each sub-pulse narrowband matched filter bank is used to perform pulse compression with the echo signal, resulting in pulse compression results corresponding to different sub-pulse matched filters. (11) in, For the first p The pulse compression results of the sub-pulse matched filter and the echo. For convolution, For the first p The time-domain impulse response of a sub-pulse matched filter.

[0048] In one embodiment, step 5 includes: calculating the peak value of all sub-pulse compression results, and using the Otsu algorithm to calculate the optimal threshold for the peak value; identifying and sorting all sub-pulses based on the optimal threshold to determine whether they have been sampled with interference; wherein sub-pulses with peak values ​​less than the optimal threshold are determined to be unsampled sub-pulses with interference, and sub-pulses with peak values ​​greater than the threshold are determined to be sampled sub-pulses with interference; and setting the narrowband matched filter of the sub-pulse corresponding to the identified sampled sub-pulses to zero and discarding it, and reconstructing a new interference mismatch filter.

[0049] In one embodiment, the reconstructed interference mismatch filter is: (12) (13) in, For the reconstructed interference mismatch filter, To identify the sorted first p The time-domain impulse response of a sub-pulse matched filter For the first p The peak value of the sub-pulse compression result. To be the optimal threshold, For the first p The time-domain impulse response of a sub-pulse matched filter To identify the first after sorting p The time-domain impulse response of a sub-pulse matched filter t For time, It represents the number of subcarriers.

[0050] In one embodiment, calculating the peak value of all sub-pulse compression results and using the Otsu algorithm to calculate the optimal threshold for the peak value includes: calculating the peak value of all sub-pulse compression results; wherein, the first... p ( p =1, 2, ..., P The peak value of the subpulse compression result corresponding to each subpulse matched filter is The interval formed by the minimum and maximum values ​​of the peak values ​​of all sub-pulse compression results is divided into average values. I Sub-intervals; placing the peak at the [number]th sub-interval; i ( i =1, 2, ..., I The peak values ​​of each sub-interval are quantized to obtain quantized values. ,in Indicates the first i Let the center value of the numerical range of interval be the nth interval. i The number of peaks in the interval is m i According to the first i Calculate the quantization value based on the number of peaks and the total number of sub-pulses within the interval. The probability of occurrence; set the threshold to the first... Quantization values ​​of each sub-interval Decomposition threshold will quantize the value Divide the data into two sets and calculate the probability of occurrence for each set; the sum of the probabilities of occurrence for the two sets is 1; calculate the quantized value for each set. Average and total quantified value Mean; the variance between two sets is defined as: ; calculate separately Value , , ..., The variance of makes To obtain the maximum value The optimal threshold is [value].

[0051] Specifically, the detailed steps for classifying and identifying whether sub-pulses have been sampled under interference using the Otsu algorithm are as follows: Step S1: Record the echo signal after the first... p ( p =1,2,…, P The peak value of the pulse after compression by the sub-pulse matched filter is ,Will The average of the interval between the minimum and maximum values ​​is divided into I There are several sub-intervals, and then the peak value is located in the first... i ( i =1,2,…, I ) intervals Quantified as , Indicates the first i Let the center value of the numerical range of interval be the nth interval. i In the interval The number of m i 。

[0052] Step S2: Calculate the quantized value The probability of occurrence is expressed as: (14) Step S3: Assume the threshold is the first... Quantization values ​​of each interval Then the quantized value in step S1 can be... Divide into two sets, namely and The probabilities of the occurrence of the two sets mentioned above are calculated as follows: (15) (16) in Represents a set A Probability of occurrence Represents a set B The probability of occurrence, and .

[0053] Step S4: Calculate the sets respectively A average and set B average and the overall mean The calculation is as follows: (17) (18) (19) Step S5: Define the set A and set B The variance between them is Calculate separately Value , , ..., The variance of makes To obtain the maximum value The optimal threshold is, i.e. (20) in, The optimal threshold is [value].

[0054] The optimal threshold is obtained through the above steps. Next, all sub-pulses are identified and sorted to determine whether they have been sampled under interference. Sub-pulses with peak values ​​below a threshold are considered unsampled, while those with peak values ​​above the threshold are considered sampled under interference. The matched filters of the identified sampled sub-pulses under interference are set to zero and discarded, and a new interference mismatch filter is reconstructed. The reconstructed interference mismatch filter and the total echo signal received by the radar are then subjected to pulse compression processing to achieve interference suppression. (twenty one) in, The result of echo pulse compression. The total echo signal received by the radar. For convolution, The reconstructed interference mismatch filter is shown in Equation (12); the time-domain impulse response of the sub-pulse matched filter is shown in Equation (13).

[0055] In a verification embodiment, to verify the effectiveness of the proposed SSFA-MCPC signal joint segmented mismatch filtering anti-jamming method, several sets of simulation comparison experiments were designed to perform interference suppression and performance evaluation analysis on three typical ISRJs. It is assumed that there is a moving target carrying a jammer in the scenario, with a target distance of 1500m and a speed of 20m / s. The radar transmission waveform and interference-related parameters in the simulation are shown in Table 1.

[0056] Table 1 Simulation Parameters

[0057] (1) Anti-ISRJ interference effect Different jamming forwarding methods produce different false target jamming effects. Simulation analysis is performed on three typical intermittent sampling forwarding jamming methods. Assuming the jammer synchronously samples and forwards the radar transmitted signal, the anti-jamming effects of the proposed method on individual ISDRJ, ISPRJ, and ISCRJ are as follows: Figure 6 , Figure 7 and Figure 8 As shown, the peak distribution formed after pulse compression of the SSFA-MCPC signal is related to the ISRJ forwarding type, and the number of peaks is consistent with the number of forwardings.

[0058] Under ISDRJ interference, the sampled signal is directly forwarded with an interference duty cycle of 0.25. Figure 8 As can be seen in (a), before interference suppression, the ISDRJ interference signal pulse compression creates a very strong false target, severely affecting the detection of the real target. And... Figure 6 In (b), after applying this method, the false target signal is effectively suppressed and cannot cause amplitude interference to the target.

[0059] Under ISPRJ interference, the number of repeated forwardings was 3, and the interference duty cycle was 0.75. Figure 7 As can be seen in (a), before interference suppression, the ISPRJ interference signal, after pulse compression, forms three consecutive main false targets, increasing the number of output interferences and increasing the peak interference value, thus achieving a certain degree of suppression and deception effect on the real targets. In contrast, from Figure 7 As can be seen in (b), after applying the interference suppression method proposed in this paper, the interference amplitude of all false targets is greatly weakened, and they are unable to cause interference to the target in terms of amplitude and quantity.

[0060] Under ISCRJ interference, in addition to forwarding the current sampling signal, it will also forward the previous signal, with a maximum interference duty cycle of 0.50. Figure 8As can be seen in (a), before interference suppression, the ISCRJ interference signal, after pulse compression, forms two continuous main false targets with different amplitudes. This is mainly because the ISCRJ will also relay the previous signal in reverse order at different time delays. Compared to... Figure 8 As can be seen in Figure (b), after applying the interference suppression method proposed in this paper, the interference amplitude of false targets is significantly reduced, and the real targets are more prominent and can be effectively identified and extracted.

[0061] (2) Evaluation of interference suppression performance In this embodiment, the signal-to-interference ratio (SJRIF) improvement factor is introduced as an evaluation index to reflect the interference suppression performance of the echo pulse compression results. The calculation formula is as follows: (twenty two) in and These represent the signal-to-interference ratio (SIR) before and after interference suppression, respectively. and These represent the maximum amplitude of the true target after interference suppression and the maximum amplitude of the false target interference, respectively. and The maximum amplitude of the true target and the maximum amplitude of the false target interference before interference suppression are given.

[0062] To verify the robustness of the proposed method against interference, experiments were conducted to analyze the variation curves of SJRIF with different SNRs under different JSR conditions for three forwarding modes. The Monte Carlo simulation was performed 100 times. The experimental results are as follows: Figure 9 As shown. Figure 9 (a) Figure 9 (b) and Figure 9 Figure (c) shows the SJRIF of ISDRJ, ISPRJ, and ISCRJ under different JSR conditions as a function of SNR, with the signal-to-noise ratio before pulse compression being [-20:5:20] dB and the signal-to-interference ratios (SIRs) being 6 dB, 9 dB, 12 dB, and 15 dB, respectively. It can be seen that at lower SNR, the echo signal is overwhelmed by noise and significantly affected by it, so the improvement in SIR is not significant. However, as the SNR increases, the improvement in SIR steadily increases under all three forwarding methods. For ISPRJ, due to the longer segment of the interfered signal in the repeated echo, it is more sensitive to noise, resulting in a slight decrease in SJRIF, but still showing a good improvement effect.

[0063] In the signal anti-ISRJ performance evaluation experiment, the SSFA-MCPC signal of this application was compared with the RR-MCPC signal proposed in the paper "Research on random redundant multi-carrier phase code signal against ISRJ based on MIMO radar" and the SCC-MCPC signal proposed in "A Radar Waveform Design of MCPC Method for Interrupted Sampling Repeater Jamming Suppression via Fractional Fourier Transform" under different SNR and JSR conditions. The Monte Carlo experiment was conducted 100 times, where SNR = [-15:5:15] dB and JSR = [6:3:15] dB. The experimental results are as follows. Figure 10 As shown, Figure 10 (a) shows the relationship between SJRIF and SNRs under the condition of JSR=6dB. Figure 10 Figure (b) shows the relationship between SJRIF and SNRs under the condition of JSR=9dB. Figure 10 (c) shows the relationship between SJRIF and SNRs under the condition of JSR=12dB. Figure 10 Figure (d) shows the relationship between SJRIF and SNRs under the condition of JSR=15dB. Figure 10 It can be seen that the proposed method has a stronger ability to resist interference compared to the MCPC single waveform design optimization method, i.e., the RR-MCPC signal. For the SCC-MCPC signal and its method, under low SNR conditions, the proposed method is affected by noise, resulting in increased sidelobes but little improvement in the signal-to-interference ratio. When the SNR is above -5dB, the SSFA-MCPC exhibits better interference suppression performance.

[0064] Furthermore, to verify the advantages of the proposed method, a comparative simulation experiment was conducted with the method used in the literature "A novel ECCM scheme against interrupted-sampling repeater jamming using intra-pulse dual-parameter agile waveform". This method, under the prior condition of known interference parameters, designs an intra-pulse dual-parameter agile LFM waveform, identifies the interfered echo slice, and then uses FrFT in the fractional domain to achieve interference suppression. The SJRIF variation curves of each method under ISDRJ, ISPRJ, and ISCRJ with different JSRs are shown below. Figure 11 As shown, where Figure 11 (a) shows the variation curve of SJRIF under ISDRJ with different JSRs. Figure 11 (b) shows the curves of SJRIF under ISPRJ with different JSRs. Figure 11 (c) shows the variation curves of SJRIF under ISCRJ with different JSRs. SNR=3dB, JSR variation range is [1:1:20]dB, and other parameters remain the same.

[0065] It can be seen that the proposed method significantly and stably improves the signal-to-interference ratio (SIR) before and after interference suppression. With the increase of the JSR (Jump Sweep Rate), the interference suppression performance also slightly improves. For ISPRJ and ISCRJ, due to repeated relaying leading to increased sidelobes and a wider distribution of false target groups compared to ISDRJ, the SIR improvement is slightly lower than that of ISDRJ, but both maintain an improvement of approximately 25-35 dB, demonstrating good interference suppression performance under the three relay modes. Compared to the proposed method in the literature, the SIR improvement for ISDRJ is significant, while for ISPRJ and ISCRJ, the interference suppression effect is similar, but still about 2-3 dB higher. However, the proposed method is limited by the need for accurate prior knowledge of interference parameters, and the method fails for phase-coded signals, thus limiting its application scenarios. In conclusion, the anti-jamming method proposed in this paper is more universal, has lower computational complexity, and is easy to implement in real-time radar systems.

[0066] It should be understood that, although the above Figure 2 The steps are shown sequentially as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise explicitly stated in this document, there is no strict order in which these steps are executed; they can be performed in other orders. Furthermore, the above... Figure 1 At least some of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0067] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0068] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and all such modifications and improvements fall within the scope of protection of this application.

Claims

1. An anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals, characterized in that, Including the following steps: The total echo signal received by the radar is converted into a baseband echo signal by a mixer. Based on the multi-carrier phase-coded signal, sub-pulse random frequency agility technology is introduced to design the SSFA-MCPC signal waveform and transmit it; The transmitted SSFA-MCPC signal is segmented by time delay to form... P Each sub-pulse signal, constructing P Sub-pulse narrowband matched filter; The baseband echo signal is passed through P Each sub-pulse narrowband matched filter performs sub-pulse segmentation pulse compression in parallel to obtain... P Subpulse compression results corresponding to each subpulse narrowband matched filter; Based on the peak characteristics of all sub-pulse compression results, the Otsu algorithm is used to adaptively identify the interfered sampled sub-pulses, remove the matched filters of the interfered sampled sub-pulses, and reconstruct the interference mismatch filter. Interference suppression is achieved by pulse compression processing of the reconstructed interference mismatch filter and the total echo signal received by the radar.

2. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, Based on multi-carrier phase-coded signals, sub-pulse random frequency agility technology is introduced to design SSFA-MCPC signal waveforms and transmit them, including: A Logistic chaotic sequence is used to perform phase coding modulation on each symbol of a traditional MCPC signal in the time domain; The frequency agility concept is introduced in the frequency domain to process the MCPC signal. Fixed-length code segments are randomly extracted from different subcarriers. The frequency agility of each segment subpulse frequency within the pulse is achieved through frequency coding modulation. The SSFA-MCPC signal waveform design is completed, and the SSFA-MCPC signal waveform is transmitted.

3. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, The complex envelope of the transmitted SSFA-MCPC signal is: in, The complex envelope of the transmitted SSFA-MCPC signal. t For time, It is the number of subcarriers; For the first p Complex weighting factors on each subcarrier, and These represent the frequency-weighted amplitude and the weighted phase, respectively. For the first p Complex envelope of subcarrier signals; For the first p Subcarrier frequencies, For the first p Random frequency coding of each subcarrier, For subcarrier frequency spacing, The duration of a single symbol; It is the number of sub-pulse symbols in each segment; For the first p On the subcarrier m Phase encoding of each chip; It is a rectangular envelope pulse; The duration of each segmented sub-pulse, the signal bandwidth, and the pulse duration are respectively... and .

4. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, The total echo signal received by the radar is: in, The total echo signal received by the radar. For the target echo signal, To intermittently sample and forward interference signals, t For time, The amplitude of the echo signal. For the target echo signal complex envelope, For the first k The echo of the radar transmitted signal sampled by the jammer during the second relay. For the target echo delay, Radar for the location and range of the scattering point target. At the speed of light, It is the number of subcarriers. p It is the first p Number of subcarriers; For the first p Subcarrier frequencies, For the first p Complex weighting factors on each subcarrier, For the first p On the subcarrier m Phase encoding of each chip, For a rectangular envelope pulse, The duration of each segmented sub-pulse, The duration of a single symbol; It is the number of sub-pulse symbols in each segment; For the amplitude of the interference signal, To interfere with echo delay, This represents Gaussian white noise. K To interfere with the number of forwards, N To determine the number of interference sampling pulses, To interfere with the sampling period, The distance between the jammer and the radar. This is the duration of the interference sampling.

5. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, The transmitted SSFA-MCPC signal is segmented by time delay to form P sub-pulse signals. P sub-pulse narrowband matched filters are then constructed, including: The transmitted SSFA-MCPC signal is divided into segments based on the sub-pulse width and time delay. P Each segment has random time-domain coding, and its spectrum is randomly distributed across different subcarriers, resulting in... P The time-domain expression of the sub-pulse signal; according to P The time-domain impulse response of each sub-pulse signal as P A sub-pulse narrowband matched filter, resulting in a... P A subpulse narrowband matched filter bank consists of several subpulse narrowband matched filters.

6. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 5, characterized in that, Among them, the first p The time-domain expression of each segmented sub-pulse signal is: in, For the first p Time-domain expression of segmented sub-pulse signals, The duration of each segmented sub-pulse, The complex envelope of the transmitted SSFA-MCPC signal. It is a rectangular envelope pulse. t For time.

7. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, Based on the peak characteristics of all sub-pulse compression results, the Otsu algorithm is used to adaptively identify the interfered sampled sub-pulses, remove the matched filters of the interfered sampled sub-pulses, and reconstruct the interference mismatch filter, including: Calculate the peak value of all sub-pulse compression results, and use the Otsu algorithm to calculate the optimal threshold for the peak value; All sub-pulses are identified and sorted based on whether they are sampled under interference according to the optimal threshold; sub-pulses with peak values ​​less than the optimal threshold are judged as unsampled sub-pulses, and sub-pulses with peak values ​​greater than the threshold are judged as sampled sub-pulses under interference. The narrowband matched filter corresponding to the identified interfered sampling sub-pulse is set to zero and discarded, and a new interference mismatch filter is reconstructed.

8. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 7, characterized in that, The reconstructed interference mismatch filter is: in, For the reconstructed interference mismatch filter, To identify the sorted first p The time-domain impulse response of a sub-pulse matched filter For the first p The peak value of the sub-pulse compression result. To be the optimal threshold, For the first p The time-domain impulse response of a sub-pulse matched filter To identify the sorted first p The time-domain impulse response of a sub-pulse matched filter t For time, It represents the number of subcarriers.

9. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 7, characterized in that, Calculate the peak value of all sub-pulse compression results, and use the Otsu algorithm to calculate the optimal threshold for the peak value, including: Calculate the peak value of all sub-pulse compression results; where, the th p The peak value of the subpulse compression result corresponding to each subpulse matched filter is , The interval formed by the minimum and maximum values ​​of the peak values ​​of all sub-pulse compression results is divided into average values. I Sub-intervals; placing the peak at the [number]th sub-interval; i ( i =1, 2, ..., I The peak values ​​of each sub-interval are quantized to obtain quantized values. ,in Indicates the first i Let the center value of the numerical range of interval be the nth interval. i The number of peaks in the interval is m i ; According to the i Calculate the quantization value based on the number of peaks and subcarriers in the interval. The probability of occurrence; Set the threshold to the [number]. Quantization values ​​of each sub-interval Decompose the threshold to quantize the value Divide the data into two sets and calculate the probability of occurrence of each set; the sum of the probabilities of occurrence of the two sets is 1. Calculate the quantization values ​​for the two sets separately. Average and total quantified value average value; Define the variance between two sets as: ; Calculate separately Value , , ..., The variance of makes To obtain the maximum value The optimal threshold is [value].

10. The anti-interference method for joint segmented mismatch filtering of SSFA-MCPC signals according to claim 1, characterized in that, Interference suppression is achieved by pulse compression processing of the reconstructed interference mismatch filter and the total echo signal received by the radar. in, The result of echo pulse compression. The total echo signal received by the radar. For convolution, For the reconstructed interference mismatch filter.

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