Distributed multi-radar collaborative anti-multi-mainlobe intermittent sampling interference method in space-time-frequency domain

Abstract

The present invention discloses a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method. First, radar signal parameters are set, the radar signal is transmitted and processed to obtain an R-D plot. Then, based on the R-D plot, the echo processing results of each sub-pulse signal are used to perform interference identification and elimination. Finally, DBSCAN is used to perform point agglomeration on the processed R-D plot to obtain target distance and speed information, thereby achieving target detection. In the absence of prior interference information, the method of the present invention can avoid interference sampling by transmitting multiple sub-pulses from multiple radars and perform interference elimination through collaborative signal processing at the receiving end. It can achieve target detection in various interference environments and has good anti-mainlobe intermittent sampling interference performance.

Description

Technical Field

[0001] The present invention belongs to the field of signal processing technology, and in particular relates to a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method. Background Art

[0002] In recent years, with the continuous development of information technology, the operating environment of radars has become increasingly complex. Ensuring that radars can function properly in such complex electronic environments has become increasingly crucial. To address the current high-intensity, diverse, and complex electromagnetic interference environment, modern radars employ various anti-interference methods, such as sidelobe blanking, sidelobe cancellation, and low sidelobe filtering. However, when interference enters the radar antenna through the mainlobe, sidelobe anti-interference methods are virtually ineffective. These methods often lead to problems such as mainlobe beam distortion and mainlobe directional deviation. Therefore, addressing the mainlobe interference issue in radars holds significant research value.

[0003] Due to the nature of intermittent sampling and forwarding interference, the interference sampling process only occurs in a portion of the time domain. Consider using multiple stations to intermittently transmit sub-pulse signals with varying pulse widths, piecing them together into a continuous wave coordinated signal in the time domain. Under this coordinated strategy, the jammer's sampling cannot guarantee that every sub-pulse signal will be sampled, and the sampling length of each sub-pulse signal is also uncertain.

[0004] The paper “W.Xiong, G.Zhang and W.Liu.'Efficient filter design against interrupted sampling repeater jamming for wideband radar'EURASIP Journal onAdvances in Signal Processing,2017(1):1-12,2017” designed a filter based on the difference in time-frequency characteristics between the target echo and ISRJ, effectively filtering out the interference signal while maintaining the integrity of the target echo. The paper “B.Fan,X.Du and W.Hu.'False targets suppression of integral power frequency modulated waveform for countering interrupted sampling repeater jamming'.IEEEGeoscience and Remote Sensing Letters,20:1-5,2023” derived the ambiguity function of the integral power frequency modulated waveform, analyzed the time-frequency characteristics of ISRJ in the range Doppler plane, and proposed an improved Doppler filtering method to suppress the interference of false targets. The above signal processing anti-interference technology focuses on suppressing interference at the radar receiving end, which is a passive anti-interference technology and does not effectively utilize the degrees of freedom of the radar system transmitting end. Summary of the Invention

[0005] To solve the above technical problems, the present invention provides a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method, which can use the echo processing results of each sub-pulse signal to perform data fusion, identify and eliminate interference, and ultimately achieve target detection.

[0006] The technical solution adopted by the present invention is: a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method, the specific steps are as follows:

[0007] S1. Set radar signal parameters and transmit radar signal;

[0008] S2, processing the signal obtained in step S1 to obtain an RD plane graph;

[0009] S3, performing interference identification and elimination based on the RD plane map obtained in step S2;

[0010] After the inter-pulse accumulation in step S2, the accumulated results are subjected to interference identification and elimination. A threshold value ψ is set, and the area in the RD result that exceeds the threshold value ψ is assigned a value of 1, and the area that does not exceed the threshold value ψ is assigned a value of 0. Then, the RD results of all sub-pulses are data fused: all areas of each RD result are logically "AND" operated to obtain the area where the real target exists.

[0011] S4. Using DBSCAN to perform point agglomeration on the RD plane graph processed in step S3 to obtain the distance and speed information of the target;

[0012] The DBSCAN algorithm includes two important parameters: neighborhood radius and minimum point count threshold. These two parameters are used to explain the definition of dense in dense areas: when the number of points within the neighborhood radius of a point is greater than the minimum point count threshold, it is considered dense.

[0013] When the DBSCAN algorithm scans the sample, it divides the sample points into three categories: core points, boundary points, and noise points:

[0014] 1) The core point is the sample point whose number of sample points within the neighborhood radius is greater than the minimum point count threshold;

[0015] 2) Boundary points are sample points that are not core points in the neighborhood of a core point;

[0016] 3) Sample points that are not core points or boundary points are noise points.

[0017] Furthermore, the step S1 is specifically as follows:

[0018] Assuming that there are M sub-pulses in one pulse, and the sub-pulse signals transmitted by each station are linear frequency modulation signals with orthogonal frequencies, the expression of the multi-sub-pulse structure signal x(t) is as follows:

[0019]

[0020] Where t represents the pulse emission time, x m (t) represents the mth sub-pulse signal, represents the emission time of the mth sub-pulse, T m represents the duration of the mth sub-pulse. m (t) The specific expression is as follows:

[0021]

[0022] Among them, f m represents the carrier frequency of the mth sub-pulse, It represents the baseband signal form of the mth sub-pulse. The specific expression is as follows:

[0023]

[0024] Among them, μ m =B / T m represents the linear frequency modulation slope of the mth sub-pulse, and B represents the bandwidth of each sub-pulse.

[0025] In a PRT, the signals transmitted by multiple transmitting stations are spliced ​​into a long pulse. In a CPI, the pulse width, timing, and bandwidth of the signals transmitted by each station are kept constant, and the expression of the single pulse x(t) is as follows:

[0026]

[0027] Assuming that there are N pulses in one CPI, the expression of the transmitted signal s(t) in one CPI is as follows:

[0028]

[0029] Among them, t n =(n-1)T, where T represents the duration of a single pulse.

[0030] Furthermore, the step S2 is specifically as follows:

[0031] S21, obtaining an echo signal;

[0032] The transmitted signal s(t) is a narrowband signal. The target distance is assumed to remain unchanged during the detection process. Considering the case of a single point target, the expression of the echo signal y(t) is as follows:

[0033]

[0034] Where c represents the speed of light, R represents the target distance, v represents the radial velocity and is much smaller than the speed of light, and the time delay is approximately τ = 2R / c.

[0035] Since the carrier frequencies of the sub-pulses are different, the wavelengths and Doppler shifts are also different. The wavelength λ corresponding to each sub-pulse is m and Doppler shift The expressions are as follows:

[0036]

[0037] S22, multi-channel pulse compression, that is, using each sub-pulse transmission signal as a different mismatch filter to perform mismatch separation with the echo;

[0038] There are M sub-pulses in a pulse. M mismatch filters h are designed based on the M sub-pulses. m ,m=1,2,...,M, use different mismatch filters and echo to perform mismatch separation.

[0039] The echo signal obtained in step S21 is y(t), which is converted into a fast and slow time dimension discrete matrix Y after sampling. Y(n,h) represents the hth sampling point of the nth pulse signal. Then the nth pulse signal of the echo passes through the output Z of the mth filter. m The expression of (n,τ) is as follows:

[0040]

[0041] S23, time domain shifting, i.e., aligning the envelopes of each mismatch separation result by time domain shifting for subsequent accumulation;

[0042] According to the emission time of different sub-pulses, the Z m (n,τ) is cyclically shifted K m Units, and truncate the signal at time 0 to obtain the result Z′ of mismatch separation after time domain shifting m (n,τ).

[0043] in, k i Represents the length of each sub-pulse after discretization.

[0044] S24, accumulating the same sub-pulses between different pulses, i.e., accumulating each sub-result using non-uniform discrete Fourier transform (NUDFT) to obtain a sub-RD graph;

[0045] For the mth sub-pulse, set the maximum unambiguous velocity to v max , uniformly sample Q points in the unambiguous velocity range and obtain the sequence v Q =[v1,v2,…,v Q ], define the row vector h m,q , the expression is as follows:

[0046]

[0047] Among them, v q =-v max +(q-1)(2v max / Q), q=1,2,…,Q.

[0048] Then construct the NUDFT transformation matrix The specific expression is as follows:

[0049]

[0050] in,() T represents the transpose of the matrix, Then the mismatch separation result Z′ of the mth sub-pulse after time domain shift is mThe NUDFT processing expression of (n,τ) is as follows:

[0051] β m (v,τ)=H m Z′ m

[0052] Among them, β m (v,τ) is the RD diagram of the mth sub-pulse.

[0053] Furthermore, the step S4 is specifically as follows:

[0054] S41, identifying core points;

[0055] For each sample point in the RD plane graph after processing in step S3, if the number of samples within its neighborhood radius (including itself) reaches or exceeds the preset minimum number of points, then this sample point is identified as a core point; then, this core point and all points within the neighborhood radius are combined to form a preliminary temporary cluster;

[0056] S42, expansion of temporary clusters;

[0057] For the temporary cluster formed in step S41, all sample points are checked. If some points are found to be core points, all points in the neighborhood radius of these points are also added to the current temporary cluster. Repeat the expansion until there are no new core points to be added. At this time, the preliminary cluster is transformed into a complete cluster.

[0058] S43, repeat step S42 to expand all temporary clusters until each point is already part of a cluster or is not in the neighborhood radius of any core point. At this time, all temporary clusters are converted into independent clusters. Finally, all sample points are in a cluster or are identified as noise points.

[0059] S44. Get target information:

[0060] Based on steps S41-S43, the average values ​​of the horizontal and vertical coordinates of all core points in each cluster are output to complete the point condensation and obtain the distance and speed information of the target;

[0061] Among them, the average value of the horizontal and vertical coordinates of all core points in the cluster is the distance and speed information of the target corresponding to the cluster.

[0062] The beneficial effects of the present invention are as follows: The method of the present invention first sets radar signal parameters, transmits and processes the radar signal to obtain an RD plane map, then uses the echo processing results of each sub-pulse signal based on the RD plane map to perform interference identification and elimination, and finally uses DBSCAN to perform point condensation on the processed RD plane map to obtain the target's distance and speed information, thereby achieving target detection. In the absence of prior interference information, the method of the present invention can avoid interference sampling by transmitting multiple sub-pulses from multiple radars and perform interference elimination through collaborative signal processing at the receiving end. It can achieve target detection in various interference environments and has good resistance to mainlobe intermittent sampling interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a flow chart of a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method of the present invention.

[0064] Figure 2 This is a time domain / frequency domain diagram of collaborative signals in a simulation scenario of space-time-frequency domain collaborative anti-single random interference in an embodiment of the present invention.

[0065] Figure 3 This is a comparison chart of the mismatch filtering results of different transmitted signals in the space-time-frequency domain collaborative anti-single random interference simulation scenario in an embodiment of the present invention.

[0066] Figure 4 This is a comparison diagram of different transmitted signals RD in a simulation scenario of collaborative anti-single random interference in the space-time-frequency domain in an embodiment of the present invention.

[0067] Figure 5 This is a comparison chart of different transmission signal threshold judgment results in the space-time-frequency domain collaborative anti-single random interference simulation scenario in an embodiment of the present invention.

[0068] Figure 6 This is a comparison chart of interference elimination results of different transmitted signals in a simulation scenario of collaborative anti-single random interference in the space-time-frequency domain in an embodiment of the present invention.

[0069] Figure 7 This is a comparison chart of the condensation results of different transmitted signal traces in the space-time-frequency domain collaborative anti-single random interference simulation scenario in an embodiment of the present invention.

[0070] Figure 8 This is a time domain / frequency domain diagram of collaborative signals in a simulation scenario of space-time-frequency domain collaborative resistance to multiple random interferences in an embodiment of the present invention.

[0071] Figure 9 This is a comparison chart of the mismatch filtering results of different transmitted signals in the simulation scenario of collaborative anti-multiple random interference in the space-time-frequency domain in an embodiment of the present invention.

[0072] Figure 10Comparison diagram of RD of different transmitted signals in a simulation scenario of collaborative anti-multiple random interferences in the space-time-frequency domain in an embodiment of the present invention.

[0073] Figure 11 Comparison of different transmit signal threshold decision results in a simulation scenario of collaborative anti-multiple random interference in the space-time-frequency domain in an embodiment of the present invention.

[0074] Figure 12 Comparison of interference elimination results of different transmitted signals in a simulation scenario of collaborative anti-multiple random interference in the space-time-frequency domain in an embodiment of the present invention.

[0075] Figure 13 A comparison chart of the condensation results of different transmitted signal traces in a simulation scenario of collaborative anti-multiple random interferences in the space-time-frequency domain in an embodiment of the present invention.

[0076] Figure 14 This is a time domain / frequency domain diagram of the collaborative signal in the space-time-frequency domain collaborative anti-single cut-1-to-1 interference simulation scenario in an embodiment of the present invention.

[0077] Figure 15 This is a comparison chart of different transmission signal mismatch filtering results in the space-time-frequency domain collaborative anti-single cut-1-to-1 interference simulation scenario in an embodiment of the present invention.

[0078] Figure 16 This is a comparison diagram of different transmission signal RDs in a simulation scenario of space-time-frequency domain collaborative anti-single cut-1-to-1 interference in an embodiment of the present invention.

[0079] Figure 17 This is a comparison chart of different transmit signal threshold judgment results in a simulation scenario of space-time-frequency domain collaborative anti-single cut-1-to-1 interference in an embodiment of the present invention.

[0080] Figure 18 This is a comparison chart of interference elimination results of different transmitted signals in a simulation scenario of collaborative anti-single cut-1-to-1 interference in the space-time-frequency domain in an embodiment of the present invention.

[0081] Figure 19 This is a comparison chart of the condensation results of different transmitted signal points in the space-time-frequency domain collaborative anti-single cut-1-to-1 interference simulation scenario in an embodiment of the present invention. DETAILED DESCRIPTION

[0082] The method of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0083] like Figure 1 As shown in FIG, a flow chart of a distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method of the present invention is shown, and the specific steps are as follows:

[0084] S1. Set radar signal parameters and transmit radar signal;

[0085] S2, processing the signal obtained in step S1 to obtain an RD plane graph;

[0086] S3, performing interference identification and elimination based on the RD plane map obtained in step S2;

[0087] After the inter-pulse accumulation in step S2, the accumulated results are subjected to interference identification and elimination. A threshold value ψ is set, and the area in the RD result that exceeds the threshold value ψ is assigned a value of 1, and the area that does not exceed the threshold value ψ is assigned a value of 0. Then, the RD results of all sub-pulses are data fused: all areas of each RD result are logically "AND" operated to obtain the area where the real target exists.

[0088] S4. Using DBSCAN to perform point agglomeration on the RD plane graph processed in step S3 to obtain the distance and speed information of the target;

[0089] The DBSCAN algorithm includes two important parameters: neighborhood radius and minimum point count threshold. These two parameters are used to explain the definition of dense in dense areas: when the number of points within the neighborhood radius of a point is greater than the minimum point count threshold, it is considered dense.

[0090] When the DBSCAN algorithm scans the sample, it divides the sample points into three categories: core points, boundary points, and noise points:

[0091] 1) The core point is the sample point whose number of sample points within the neighborhood radius is greater than the minimum point count threshold;

[0092] 2) Boundary points are sample points that are not core points in the neighborhood of a core point;

[0093] 3) Sample points that are not core points or boundary points are noise points.

[0094] In this embodiment, step S1 is specifically as follows:

[0095] Assuming that there are M sub-pulses in one pulse, and the sub-pulse signals transmitted by each station are linear frequency modulation signals with orthogonal frequencies, the expression of the multi-sub-pulse structure signal x(t) is as follows:

[0096]

[0097] Where t represents the pulse emission time, x m (t) represents the mth sub-pulse signal, represents the emission time of the mth sub-pulse, T m represents the duration of the mth sub-pulse. m (t) The specific expression is as follows:

[0098]

[0099] Among them, f m represents the carrier frequency of the mth sub-pulse, It represents the baseband signal form of the mth sub-pulse. The specific expression is as follows:

[0100]

[0101] Among them, μ m =B / T m represents the linear frequency modulation slope of the mth sub-pulse, and B represents the bandwidth of each sub-pulse.

[0102] In a PRT, the signals transmitted by multiple transmitting stations are spliced ​​into a long pulse. In a CPI, the pulse width, timing, and bandwidth of the signals transmitted by each station are kept constant, and the expression of the single pulse x(t) is as follows:

[0103]

[0104] Assuming that there are N pulses in one CPI, the expression of the transmitted signal s(t) in one CPI is as follows:

[0105]

[0106] Among them, t n =(n-1)T, where T represents the duration of a single pulse.

[0107] In this embodiment, step S2 is specifically as follows:

[0108] S21, obtaining an echo signal;

[0109] The transmitted signal s(t) is a narrowband signal. The target distance is assumed to remain unchanged during the detection process. Considering the case of a single point target, the expression of the echo signal y(t) is as follows:

[0110]

[0111] Where c represents the speed of light, R represents the target distance, v represents the radial velocity and is much smaller than the speed of light, and the time delay is approximately τ = 2R / c.

[0112] Since the carrier frequencies of the sub-pulses are different, the wavelengths and Doppler shifts are also different. The wavelength λ corresponding to each sub-pulse is m and Doppler shift The expressions are as follows:

[0113]

[0114] S22, multi-channel pulse compression, that is, using each sub-pulse transmission signal as a different mismatch filter to perform mismatch separation with the echo;

[0115] There are M sub-pulses in a pulse. M mismatch filters h are designed based on the M sub-pulses. m ,m=1,2,...,M, use different mismatch filters and echo to perform mismatch separation.

[0116] The echo signal obtained in step S21 is y(t), which is converted into a fast and slow time dimension discrete matrix Y after sampling. Y(n,h) represents the hth sampling point of the nth pulse signal. Then the nth pulse signal of the echo passes through the output Z of the mth filter. m The expression of (n,τ) is as follows:

[0117]

[0118] S23, time domain shifting, i.e., aligning the envelopes of each mismatch separation result by time domain shifting for subsequent accumulation;

[0119] According to the emission time of different sub-pulses, the Z m (n,τ) is cyclically shifted K m Units, and truncate the signal at time 0 to obtain the result Z′ of mismatch separation after time domain shifting m (n,τ).

[0120] in, k i Represents the length of each sub-pulse after discretization.

[0121] S24, accumulating the same sub-pulses between different pulses, i.e., accumulating each sub-result using non-uniform discrete Fourier transform (NUDFT) to obtain a sub-RD graph;

[0122] For the mth sub-pulse, set the maximum unambiguous velocity to v max , uniformly sample Q points in the unambiguous velocity range and obtain the sequence v Q =[v1,v2,…,v Q ], define the row vector h m,q , the expression is as follows:

[0123]

[0124] Among them, v q =-v max +(q-1)(2v max / Q), q=1,2,…,Q;

[0125] Then construct the NUDFT transformation matrix The specific expression is as follows:

[0126]

[0127] in,() T represents the transpose of the matrix, Then the mismatch separation result Z′ of the mth sub-pulse after time domain shift is m The NUDFT processing expression of (n,τ) is as follows:

[0128] β m (v,τ)=H m Z′ m

[0129] Among them, β m (v,τ) is the RD diagram of the mth sub-pulse.

[0130] In this embodiment, step S4 is specifically as follows:

[0131] S41, identifying core points;

[0132] For each sample point in the RD plane graph after processing in step S3, if the number of samples within its neighborhood radius (including itself) reaches or exceeds the preset minimum number of points, then this sample point is identified as a core point; then, this core point and all points within the neighborhood radius are combined to form a preliminary temporary cluster;

[0133] S42, expansion of temporary clusters;

[0134] For the temporary cluster formed in step S41, all sample points are checked. If some points are found to be core points, all points in the neighborhood radius of these points are also added to the current temporary cluster. Repeat the expansion until there are no new core points to be added. At this time, the preliminary cluster is transformed into a complete cluster.

[0135] S43, repeat step S42 to expand all temporary clusters until each point is already part of a cluster or is not in the neighborhood radius of any core point. At this time, all temporary clusters are converted into independent clusters. Finally, all sample points are in a cluster or are identified as noise points.

[0136] S44. Get target information:

[0137] Based on steps S41-S43, the average values ​​of the horizontal and vertical coordinates of all core points in each cluster are output to complete the point condensation and obtain the distance and speed information of the target;

[0138] Among them, the average value of the horizontal and vertical coordinates of all core points in the cluster is the distance and speed information of the target corresponding to the cluster.

[0139] This embodiment further conducts simulation verification and analysis, including: space-time-frequency domain collaborative resistance to single random interference, space-time-frequency domain collaborative resistance to multiple random interferences, and space-time-frequency domain collaborative resistance to single cut-1-to-1 interference, as follows:

[0140] (1) Space-time-frequency domain collaborative anti-single random interference;

[0141] The simulation parameters of this embodiment are set as follows: the target distance and speed are set to 160km and 200m / s, and the space-time-frequency domain anti-interference detection parameters are set as follows: the radar carrier frequency is 3GHz, and the available bandwidth of the cooperative signal is B s =800MHz, cooperative signal pulse repetition time T p′ =100μs, the number of repeated pulses in CPI is 64, the sub-pulse width range of a single site is [5μs, 20μs], the first frequency point of the sub-pulse signal f1 = 40MHz, the frequency point spacing of the sub-pulse signal Δf = 80MHz, and the bandwidth of the sub-pulse signal B p =20MHz, SNR = 0dB, JNR = 15dB. Compare this with a conventional LFM signal with a time width of 100μs, a bandwidth of 20MHz, and a carrier frequency of 3GHz.

[0142] After receiving the signal, the adversary jammer samples and forwards it with random jamming sampling durations and sampling periods within a certain range. There is also a random jamming generation interval: when the current jamming generation time reaches the jamming sampling interval, another jamming signal is randomly generated. Each jamming signal pattern is randomly selected between ISDRJ, ISPRJ, and ISCRJ. The jamming parameters of the adversary jammer are set as follows: the jamming sampling duration is randomly selected between [2μs, 5μs], the jamming sampling period is randomly selected between [10μs, 20μs], and the jamming generation interval is randomly selected between [80μs, 150μs].

[0143] Simulation analysis: Figure 2 As shown, Figure 2 (a) is the time domain diagram of the cooperative signal. Figure 2 (b) shows the frequency domain diagram of the coordinated signal. The coordinated signal in the time domain consists of multiple sub-pulses spliced ​​together into a long pulse, with the frequencies of the sub-pulses being orthogonal to each other. When the jammer receives the coordinated signal and is unable to discern specific interference from the time and frequency domains, it samples the signal from the moment it first receives it, performing intermittent sampling and forwarding interference.

[0144] like Figure 3 As shown, Figure 3 (a) is the cooperative signal mismatch filtering result, Figure 3 (b) is the result of traditional LFM signal mismatch filtering. Figure 3(a) It can be seen that when transmitting space-time-frequency domain coordinated signals, false target information appears in the mismatch filtering results because the sub-pulse signals are sampled by interference. However, since the sampled sub-pulse signals are different, the interference manifestations in each filtering result are different, and the interference can be identified and processed based on this. Figure 3 (b) It can be seen that when transmitting the traditional existing LFM signal, the mismatch filtering result is greatly affected by the interference signal.

[0145] like Figure 4 As shown, Figure 4 (a), (b), and (c) are the 1st, 2nd, and 3rd sub-pulses RD of the cooperative signal, respectively. Figure 4 (d) is the traditional LFM signal RD, Figure 4 (a), (b), and (c) show that the jammer can sample the sub-pulse signal and reflect it as false target information on the RD diagram. When transmitting the space-time-frequency domain cooperative signal, the sub-pulse signal corresponding to certain moments will be severely sampled, resulting in a large amount of interference information in the result of the sub-pulse signal processing, such as Figure 4 (b); At the same time, there are also cases where only a small part of some sub-pulse signals is sampled by interference, and the interference component on the RD graph result is weakened compared with other results, such as Figure 4 (a) Each RD graph is then judged and processed, first removing interference with lower amplitudes, and then performing interference identification and elimination based on the judgment results.

[0146] like Figure 5 As shown, Figure 5 (a), (b), and (c) are the threshold decision results of the 1st, 2nd, and 3rd sub-pulses of the cooperative signal, respectively. Figure 5 (d) is the traditional LFM signal threshold judgment result. Figure 5 As can be seen from (a), (b), and (c), when transmitting space-time-frequency domain cooperative signals, the results obtained by each RD diagram after threshold judgment are different, but all have values ​​near the target parameter position (distance 160km, speed 200m / s). Therefore, interference identification and elimination can be performed based on all judgment results, that is, the positions where all judgment results have values ​​are considered to have targets, and the rest are interference, thereby eliminating interference at different positions.

[0147] like Figure 6 As shown, Figure 6 (a) is the result of cooperative signal interference elimination, Figure 6 (b) is the result of traditional LFM signal interference elimination. Figure 6(a) It can be seen that when transmitting space-time-frequency domain coordinated signals, after the interference is eliminated, the interference items on the threshold judgment result are cleared, and detection results only exist in a small range near 160km and 200m / s. The space-time-frequency domain anti-interference detection mission is basically successful, and the influence of intermittent sampling forwarding interference is successfully suppressed.

[0148] like Figure 7 As shown, Figure 7 (a) is the result of collaborative signal trace aggregation, Figure 7 (b) is the result of traditional LFM signal trace aggregation. Figure 7 (a) It can be seen that when transmitting space-time-frequency domain coordinated signals, after the point traces are condensed, the condensation result shows that there is a point target at 160 km and 200 m / s, which is consistent with the simulation parameter settings, verifying the effectiveness of the method of the present invention.

[0149] From Figures 4(d), 5(d), 6(b), and 7(b), it can be seen that the target position cannot be correctly obtained when the traditional LFM signal is transmitted.

[0150] (2) Collaborative anti-multiple random interference in space-time-frequency domain;

[0151] The simulation parameters of this embodiment are as follows: the target distance and speed are set to 100km and 150m / s, and the space-time-frequency domain anti-interference detection parameters are set as follows: the radar carrier frequency is 3GHz, and the available bandwidth of the cooperative signal is B. s =800MHz, cooperative signal pulse repetition time T p′ =100μs, the number of repeated pulses in CPI is 64, the sub-pulse width range of a single site is [5μs, 20μs], the first frequency point of the sub-pulse signal f1 = 40MHz, the frequency point spacing of the sub-pulse signal Δf = 80MHz, and the bandwidth of the sub-pulse signal B p =20MHz, SNR = 0dB, JNR = 15dB. Compare this with a conventional LFM signal with a time width of 100μs, a bandwidth of 20MHz, and a carrier frequency of 3GHz.

[0152] Consider an adversary with three jammers, each operating independently. After receiving a signal, the adversary jammer samples and forwards it with random jamming sampling durations and sampling periods within a certain range. There is also a random jamming generation interval: when the current jamming generation time reaches the jamming sampling interval, another jamming signal is randomly generated. Each jamming signal pattern is randomly selected between ISDRJ, ISPRJ, and ISCRJ. The jamming parameters of the adversary jammer are set as follows: the jamming sampling duration is randomly selected between [2μs, 5μs], the jamming sampling period is randomly selected between [10μs, 20μs], and the jamming generation interval is randomly selected between [80μs, 150μs].

[0153] Simulation analysis: Figure 8 As shown, Figure 8 (a) is the time domain diagram of the cooperative signal. Figure 8 (b) shows the frequency domain diagram of the coordinated signal. The coordinated signal in the time domain consists of multiple sub-pulses spliced ​​together into a long pulse, with the frequencies of the sub-pulses being orthogonal to each other. When the jammer receives the coordinated signal and is unable to discern specific interference from the time and frequency domains, it samples the signal from the moment it first receives it, performing intermittent sampling and forwarding interference.

[0154] like Figure 9 As shown, Figure 9 (a) is the cooperative signal mismatch filtering result, Figure 9 (b) is the result of traditional LFM signal mismatch filtering. Figure 9 (a) It can be seen that when transmitting space-time-frequency domain cooperative signals, false target information appears in the mismatch filtering results because the sub-pulse signal is sampled by interference. Compared with the case of single interference, in the case of multiple interference, more false target information caused by interference signals appears in the mismatch filtering results. Figure 9 (b) It can be seen that when transmitting traditional LFM signals, the mismatch filtering result is greatly affected by the interference signal.

[0155] like Figure 10 As shown, Figure 10 (a), (b), and (c) are the 1st, 2nd, and 3rd sub-pulses RD of the cooperative signal, respectively. Figure 10 (d) is the traditional LFM signal RD, Figure 10 (a), (b), and (c) show that the jammer can sample the sub-pulse signal and reflect it as false target information on the RD diagram. When transmitting space-time-frequency domain coordinated signals, the sub-pulse signal corresponding to certain moments will be severely sampled, resulting in a large amount of interference information in the sub-pulse signal processing results.

[0156] like Figure 11 As shown, Figure 11 (a), (b), and (c) are the threshold decision results of the 1st, 2nd, and 3rd sub-pulses of the cooperative signal, respectively. Figure 11 (d) is the traditional LFM signal threshold judgment result. Figure 11 As can be seen from (a), (b), and (c), when transmitting space-time-frequency domain cooperative signals, the results of each RD diagram after passing the threshold judgment are different. Compared with the single interference case, in the multiple interference case, more false target information caused by the interference signal appears in the RD diagram, but all of them have values ​​near the target parameter position (distance 100km, speed 150m / s). Therefore, interference identification and elimination can be performed based on all the judgment results, that is, the positions where all the judgment results have values ​​are considered to have targets, and the rest are interference, thereby eliminating the interference at different positions.

[0157] like Figure 12 As shown, Figure 12 (a) is the result of cooperative signal interference elimination, Figure 12 (b) is the result of traditional LFM signal interference elimination. Figure 12 As shown in Figure 1, when transmitting a coordinated signal in the space-time-frequency domain, the interference term on the threshold decision result is eliminated after the interference is eliminated. Detection results only exist in a small range near 100 km and 150 m / s. The space-time-frequency domain anti-interference detection mission is basically successful, and the impact of intermittent sampling and forwarding interference is successfully suppressed.

[0158] like Figure 13 As shown, Figure 13 (a) is the result of collaborative signal trace aggregation, Figure 13 (b) is the result of traditional LFM signal trace aggregation. Figure 13 (a) It can be seen that when transmitting space-time-frequency domain coordinated signals, after the point traces are condensed, the condensation result shows that there is a point target at 99.9997 km and 150 m / s, which is consistent with the simulation parameter settings, verifying the effectiveness of the method of the present invention.

[0159] from Figure 10 (d), 11(d), 12(b), and 13(b) show that the target position cannot be correctly obtained when the traditional LFM signal is transmitted.

[0160] (3) Space-time-frequency domain collaborative anti-single cut-1-to-1 interference;

[0161] The simulation parameters of this embodiment are set as follows: the target distance and speed are set to 100km and 100m / s, and the space-time-frequency domain anti-interference detection parameters are set as follows: the radar carrier frequency is 3GHz, and the cooperative signal available bandwidth B s =800MHz, cooperative signal pulse repetition time T p′=100μs, the number of repeated pulses in CPI is 64, the sub-pulse width range of a single site is [5μs, 20μs], the first frequency point of the sub-pulse signal f1 = 40MHz, the frequency point spacing of the sub-pulse signal Δf = 80MHz, and the bandwidth of the sub-pulse signal B p =20MHz, SNR = 0dB, JNR = 15dB. Compare this with a conventional LFM signal with a time width of 100μs, a bandwidth of 20MHz, and a carrier frequency of 3GHz.

[0162] The known operating limit of current jammers is to sample 1μs and then immediately forward the sampled 1μs slice. Therefore, after the adversary jammer receives the signal, it samples and forwards it in a "1μs to 1μs" manner.

[0163] Simulation analysis: Figure 14 As shown, Figure 14 (a) is the time domain diagram of the cooperative signal. Figure 14 (b) shows the frequency domain diagram of the coordinated signal. The coordinated signal in the time domain consists of multiple sub-pulses spliced ​​together into a long pulse, with the frequencies of the sub-pulses being orthogonal to each other. When the jammer receives the coordinated signal and is unable to discern specific interference from the time and frequency domains, it samples the signal from the moment it first receives it, performing intermittent sampling and forwarding interference.

[0164] like Figure 15 As shown, Figure 15 (a) is the cooperative signal mismatch filtering result, Figure 15 (b) is the result of traditional LFM signal mismatch filtering; Figure 16 As shown, Figure 16 (a), (b), and (c) are the 1st, 2nd, and 3rd sub-pulses RD of the cooperative signal, respectively. Figure 16 (d) is the traditional LFM signal RD; Figure 17 As shown, Figure 17 (a), (b), and (c) are the threshold decision results of the 1st, 2nd, and 3rd sub-pulses of the cooperative signal, respectively. Figure 17 (d) is the traditional LFM signal threshold judgment result.

[0165] from Figure 15 (a), 16(a), (b), (c), 17(a), (b), (c) show that when the jammer speeds up the sampling rhythm, the probability of the sub-pulse signal being sampled increases, making it difficult to obtain target information in the intermediate process of signal processing.

[0166] like Figure 18 As shown, Figure 18 (a) is the result of cooperative signal interference elimination, Figure 18 (b) is the result of traditional LFM signal interference elimination; Figure 19 As shown, Figure 19 (a) is the result of collaborative signal trace aggregation, Figure 19 (b) is the result of traditional LFM signal trace aggregation.

[0167] from Figure 18 As shown in Figures 19(a), after interference removal and point trace condensation, the condensation results show a point target at 100.15 km and 100 m / s, which is consistent with the simulation parameter settings and verifies the effectiveness of the proposed method. Although the jammer's accelerated sampling rhythm affects the probability of each sub-pulse being sampled and the signal processing results of the sub-pulse, the subsequent coordinated signal processing of the collaborative strategy can still obtain true target information.

[0168] from Figure 15 (b), 16(d), 17(d), 18(b), and 19(b) show that the target position cannot be correctly obtained when the traditional LFM signal is transmitted.

[0169] In summary, compared with traditional LFM signals, the distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method proposed by the method of the present invention can avoid interference sampling by transmitting multiple sub-pulses by multiple radars and perform collaborative signal processing at the receiving end in the absence of prior interference information. It can detect targets in various interference environments and has good anti-mainlobe intermittent sampling interference performance.

[0170] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method, the specific steps are as follows: S1. Set radar signal parameters and transmit radar signal; Assume that there are M sub-pulses in one pulse, and the sub-pulse signals transmitted by each station are linear frequency modulation signals with orthogonal frequencies; S2, processing the signal obtained in step S1 to obtain an RD plane graph; S21, obtaining an echo signal; S22, multi-channel pulse compression, that is, using each sub-pulse transmission signal as a different mismatch filter to perform mismatch separation with the echo; S23, time domain shifting, i.e., aligning the envelopes of each mismatch separation result by time domain shifting for subsequent accumulation; S24, accumulating the same sub-pulses between different pulses, i.e., accumulating each sub-result using non-uniform discrete Fourier transform (NUDFT) to obtain a sub-RD graph; S3, performing interference identification and elimination based on the RD plane map obtained in step S2; After inter-pulse accumulation in step S2, interference identification and elimination are performed on the accumulated results. A threshold value ψ is set. Regions in the RD result exceeding the threshold value ψ are assigned a value of 1, while regions below the threshold value ψ are assigned a value of 0. The RD results of all sub-pulses are then fused: a logical "AND" operation is performed on all regions of each RD result to obtain the region where the actual target exists. S4. Using DBSCAN to perform point agglomeration on the RD plane graph processed in step S3 to obtain the distance and speed information of the target; The DBSCAN algorithm includes two important parameters: neighborhood radius and minimum point count threshold. These two parameters are used to explain the definition of dense in dense areas: when the number of points within the neighborhood radius of a point is greater than the minimum point count threshold, it is considered dense. When scanning samples, the DBSCAN algorithm divides the sample points into three categories: core points, boundary points, and noise points. It outputs the average value of the horizontal and vertical coordinates of all core points in each cluster, completes point condensation, and obtains the distance and speed information of the target.

2. The distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method according to claim 1 is characterized in that: The step S1 is specifically as follows: The expression of the multi-sub-pulse structure signal x(t) is as follows: Where t represents the pulse emission time, x m (t) represents the mth sub-pulse signal, represents the emission time of the mth sub-pulse, T m represents the duration of the mth sub-pulse; x m (t) The specific expression is as follows: Among them, f m represents the carrier frequency of the mth sub-pulse, It represents the baseband signal form of the mth sub-pulse. The specific expression is as follows: Among them, μ m =B / T m represents the linear frequency modulation slope of the mth sub-pulse, and B represents the bandwidth of each sub-pulse; In a PRT, the signals transmitted by multiple transmitting stations are spliced ​​into a long pulse. In a CPI, the pulse width, timing, and bandwidth of the signals transmitted by each station are kept constant, and the expression of the single pulse x(t) is as follows: Assuming that there are N pulses in one CPI, the expression of the transmitted signal s(t) in one CPI is as follows: Among them, t n =(n-1)T, where T represents the duration of a single pulse.

3. The distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method according to claim 1 is characterized in that: The step S2 is specifically as follows: S21, obtaining an echo signal; The transmitted signal s(t) is a narrowband signal. The target distance is assumed to remain unchanged during the detection process. Considering the case of a single point target, the expression of the echo signal y(t) is as follows: Where c represents the speed of light, R represents the target distance, v represents the radial velocity and is much smaller than the speed of light, and the time delay is approximately τ = 2R / c; Since the carrier frequencies of the sub-pulses are different, the wavelengths and Doppler shifts are also different. The wavelength λ corresponding to each sub-pulse is m and Doppler shift The expressions are as follows: S22, multi-channel pulse compression, that is, using each sub-pulse transmission signal as a different mismatch filter to perform mismatch separation with the echo; There are M sub-pulses in a pulse. M mismatch filters h are designed based on the M sub-pulses. m ,m=1,2,...,M, use different mismatch filters and echoes for mismatch separation; The echo signal obtained in step S21 is y(t), which is converted into a fast and slow time dimension discrete matrix Y after sampling. Y(n,h) represents the hth sampling point of the nth pulse signal. Then the nth pulse signal of the echo passes through the output Z of the mth filter. m The expression of (n,τ) is as follows: S23, time domain shifting, i.e., aligning the envelopes of each mismatch separation result by time domain shifting for subsequent accumulation; According to the emission time of different sub-pulses, the Z m (n,τ) is cyclically shifted K m Units, and truncate the signal at time 0 to obtain the result Z′ of mismatch separation after time domain shifting m (n,τ); in, k i Represents the length of each sub-pulse after discretization; S24, accumulating the same sub-pulses between different pulses, i.e., accumulating each sub-result using non-uniform discrete Fourier transform (NUDFT) to obtain a sub-RD graph; For the mth sub-pulse, set the maximum unambiguous velocity to v max , uniformly sample Q points in the unambiguous velocity range and obtain the sequence v Q =[v1,v2,…,v Q ], define the row vector h m,q , the expression is as follows: Among them, v q =-v max +(q-1)(2v max / Q), q=1,2,…,Q; Then construct the NUDFT transformation matrix The specific expression is as follows: in,() T represents the transpose of the matrix, Then the mismatch separation result Z′ of the mth sub-pulse after time domain shift is m The NUDFT processing expression of (n,τ) is as follows: β m (v,τ)=H m Z′ m Among them, β m (v,τ) is the RD diagram of the mth sub-pulse.

4. The distributed multi-radar space-time-frequency domain collaborative anti-multi-mainlobe intermittent sampling interference method according to claim 1 is characterized in that: The step S4 is specifically as follows: S41, identifying core points; For each sample point in the RD plane graph processed in step S3, if the number of samples within its neighborhood radius reaches or exceeds the preset minimum number of points, then this sample point is identified as a core point; then, this core point and all points within the neighborhood radius are combined to form a preliminary temporary cluster; S42, expansion of temporary clusters; For the temporary cluster formed in step S41, all sample points are checked. If some points are found to be core points, all points in the neighborhood radius of these points are also added to the current temporary cluster. Repeat the expansion until there are no new core points to be added. At this time, the preliminary cluster is transformed into a complete cluster. S43, repeat step S42 to expand all temporary clusters until each point is already part of a cluster or is not in the neighborhood radius of any core point. At this time, all temporary clusters are converted into independent clusters. Finally, all sample points are in a cluster or are identified as noise points. S44. Get target information: Based on steps S41-S43, the average values ​​of the horizontal and vertical coordinates of all core points in each cluster are output to complete the point condensation and obtain the distance and speed information of the target; Among them, the average value of the horizontal and vertical coordinates of all core points in the cluster is the distance and speed information of the target corresponding to the cluster.

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