A multi-radar signal cooperative anti-multi-main-lobe intermittent sampling interference method

Abstract

This application discloses a method for combating multi-main-lobe intermittent sampling interference through multi-radar signal coordination, relating to the field of signal processing technology. It includes: expanding the summation or integration process of the matched filtering results of the signals received by M receiving nodes of a radar system along its expanded dimensions, and performing interference suppression processing along the expanded dimensions to obtain the filter output; sampling the filter output after range gate alignment, and converting it into a fast and slow time-dimensional matrix with A sampling points; performing Q-point coherent accumulation within each of the M receiving nodes' received signals, and combining this with the fast and slow time-dimensional matrix to obtain an R-D diagram of the M receiving nodes; performing P-point coherent accumulation between the receiving nodes on the R-D diagram of the M receiving nodes to obtain a two-dimensional matrix, and taking the x and y coordinates corresponding to the maximum value of the two-dimensional matrix as the target's range and velocity. This method addresses how to effectively suppress multiple intermittent sampling interferences in the absence of prior interference information.

Description

Technical Field

[0001] This application relates to the field of signal processing technology, and in particular to a method for coordinating multiple radar signals to resist intermittent sampling interference of multiple main lobes. Background Technology

[0002] Interference has always been a key factor limiting the performance of modern radar systems in detection, estimation, tracking, and imaging tasks. Based on its location in the beam pattern, interference can be mainly divided into two categories: sidelobe interference and mainlobe interference. Modern radars employ various anti-interference methods to combat sidelobe interference, such as sidelobe masking, sidelobe cancellation, and low sidelobe techniques. However, traditional sidelobe anti-interference methods for mainlobe interference can lead to problems such as mainlobe shift. Therefore, researching new methods to suppress mainlobe interference is crucial for improving the survivability and detection performance of radar systems under mainlobe interference conditions.

[0003] The paper "Y Li, J Wang, Y Wang, et al. Random-frequency-Coded waveform optimization and signal coherent accumulation against compound deception jamming[J]. IEEE Trans. Aerosp. Electron. Syst., 2023, 59(4): 4434-4449" constructs an inter-pulse-intra-pulse joint frequency-coded waveform, achieving effective suppression of multi-deception interference. The paper "Y Gao, H Fan, LRen, et al. Joint design of waveform and mismatched filter for interrupted sampling repeater jamming suppression[J]. IEEE Trans. Aerosp. Electron.Syst., 2023" improves target detection performance under intermittent sampling interference by jointly optimizing the intra-pulse parameters of the transmitted waveform and the mismatched filter based on the objective function of suppressing interference. However, the above anti-interference techniques require accurate prior information about the interference. Summary of the Invention

[0004] The purpose of this application is to provide a method for coordinating multiple radar signals to resist multi-main-lobe intermittent sampling interference, in order to solve how to effectively suppress multiple intermittent sampling interferences in the absence of prior information about the interference.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] On the one hand, this application provides a method for combating multi-main-lobe intermittent sampling interference through multi-radar signal coordination, including:

[0007] S1. Perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by the M receiving nodes of the radar system, and perform interference suppression processing along the expanded dimension to obtain the filter output results of the M receiving nodes.

[0008] S2. After performing range gate alignment processing on the filter output results of the M receiving nodes, sample the results and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A.

[0009] S3. Multi-channel discrete Fourier transform is used to perform Q-point coherent accumulation of the received signals of M receiving nodes, and the RD diagram of M receiving nodes is obtained by combining the fast and slow time dimension matrix.

[0010] S4. Perform P-point coherent accumulation between the M receiving nodes using Fast Fourier Transform to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

[0011] On the other hand, this application also provides a multi-radar signal coordinated anti-multi-main-lobe intermittent sampling interference device, comprising:

[0012] The pulse compression module is used to perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by M receiving nodes of the radar system, and to perform interference suppression processing along the expanded dimension to obtain the filter output results of M receiving nodes.

[0013] The distance gate alignment module is used to perform distance gate alignment processing on the filter output results of the M receiving nodes and then sample them, and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A.

[0014] The first coherent accumulation module is used to perform Q-point coherent accumulation of the received signals of M receiving nodes using multi-channel discrete Fourier transform, and to obtain the RD diagram of M receiving nodes by combining the fast and slow time dimension matrix.

[0015] The second coherent accumulation module is used to perform P-point coherent accumulation between the M receiving nodes using a fast Fourier transform on the RD graphs of the receiving nodes, to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

[0016] Based on the above technical solution, this application can achieve the following technical effects:

[0017] To address intermittent sampling interference, a cooperative transmission processing technique based on multi-static radars is proposed to combat multi-main-lobe intermittent sampling interference. The method involves each radar node transmitting a pulse signal with a different time width and orthogonal frequency domain, which is then concatenated in the time domain to form a continuous signal. Due to the characteristics of intermittent sampling interference, the jammer can intercept a portion of the target signal. By utilizing the multi-pulse structure, the interception length of a single transmitted signal can be reduced, thereby decreasing the interference level on individual transmitted signals. Then, leveraging the jammer's partial interception characteristic, the interference is filtered out during matched filtering. Furthermore, subsequent coherent accumulation within a single radar node and coherent accumulation across multiple radar nodes further highlight the range and velocity information of the true target. This approach effectively suppresses intermittent sampling interference without requiring prior knowledge of the interference. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a method for combating multi-main-lobe intermittent sampling interference through multi-radar signal coordination, provided in an embodiment of this application.

[0019] Figure 2 A simulation of the cooperative signal time-domain / frequency-domain plot provided in an embodiment of this application;

[0020] Figure 3 Simulation results of different transmitted signal pulse compressions provided in an embodiment of this application;

[0021] Figure 4 Simulation 1 shows different receiving node RD diagrams for one embodiment of this application;

[0022] Figure 5 The simulation 1 provided for different transmitted signals and the final output RD diagram are shown in one embodiment of this application.

[0023] Figure 6 Simulation 2 provides a time-domain / frequency-domain diagram of the cooperative signal in one embodiment of this application;

[0024] Figure 7 Simulation results of different transmitted signal pulse compressions provided in one embodiment of this application;

[0025] Figure 8 Simulation 2 shows different receiving node RD diagrams provided for one embodiment of this application;

[0026] Figure 9 The simulation results for different transmitted signals in an embodiment of this application are shown in the RD diagram. Detailed Implementation

[0027] The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present application will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and are not to scale, and are only used to facilitate and clarify the illustration of the embodiments of the present application.

[0028] It should be noted that, in order to clearly illustrate the content of this application, several embodiments are provided to further explain the different implementations of this application. These embodiments are enumerated rather than exhaustive. Furthermore, for the sake of brevity, content mentioned in the preceding embodiments is often omitted in the following embodiments. Therefore, content not mentioned in the following embodiments can be referred to in the preceding embodiments.

[0029] Example 1

[0030] Please refer to Figure 1 , Figure 1 The diagram shown is a flowchart illustrating a multi-radar signal coordinated method for combating intermittent sampling interference of multiple main lobes provided in this embodiment. The method specifically includes the following steps:

[0031] S1. Perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by the M receiving nodes of the radar system, and perform interference suppression processing along the expanded dimension to obtain the filter output results of the M receiving nodes.

[0032] It should be noted that one possible implementation of step S1 is as follows:

[0033] S11. Expand the summation or integration process of the matched filtering results of the signals received by the M receiving nodes of the radar system in a dimensional manner to obtain the two-dimensional matched filtering results of the signals received by the M receiving nodes.

[0034] S12. Iterate through the two-dimensional matched filtering results of the received signals at each receiving node along the time delay. Determine the time delay corresponding to the target, the time delay corresponding to the interference, and the time delay corresponding to the target plus interference based on the amplitude of the two-dimensional matched filtering results in the unfolded dimension. Set the two-dimensional matched filtering results at the time delay corresponding to the interference and the time delay corresponding to the target plus interference to 0 to obtain the two-dimensional matched filtering results after interference suppression.

[0035] S13. The two-dimensional matched filtering result after interference suppression is summed along the unfolded dimension to obtain the filter output results of M receiving nodes.

[0036] Furthermore, in S12, the time delay corresponding to the target, the time delay corresponding to the interference, and the time delay corresponding to the target plus interference are determined based on the magnitude of the two-dimensional matched filtering result in the unfolded dimension. Specifically, this includes the following steps:

[0037] S12-1. Determine whether the two-dimensional matched filtering result at the current time delay has an amplitude in the unfolded dimension;

[0038] S12-2. If all values ​​have amplitude, then determine that the current time delay is the time delay corresponding to the target. If not all values ​​have amplitude, then determine whether the two-dimensional matched filtering result at the current time delay has amplitude in only some regions in the unfolded dimension, and whether the amplitude in other regions is close to 0.

[0039] S12-3. If yes, then determine that the current delay is the delay corresponding to the interference; if no, then determine that the current delay is the delay corresponding to the overlap of the target and the interference.

[0040] S12-4. Sequentially determine whether the amplitude of the two-dimensional matched filtering result at the time delay corresponding to the overlap of the target and the interference is greater than the average amplitude at that time delay.

[0041] S12-5. If the current delay is greater than the average amplitude, then the current delay is determined to be the delay corresponding to the target plus interference. If the current delay is less than the average amplitude, then the current delay is determined to be the delay corresponding to the target.

[0042] Furthermore, preceding S12-4, it also includes:

[0043] The mean amplitude at the time delay corresponding to the overlap of the target and the interference is obtained by summing the amplitudes of the two-dimensional matched filtering results in the unfolded dimension and dividing by the length of the unfolded dimension.

[0044] Based on this, when transmitting coordinated signals, each receiving node can directly filter out most of the interference while performing pulse compression using this interference suppression method.

[0045] S2. After performing range gate alignment processing on the filter output results of the M receiving nodes, sample the results and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A.

[0046] It should be noted that one possible implementation of step S2 is as follows:

[0047] S21. Based on the filter output of the first receiving node and the known pulse duration of the transmitted signal, calculate the time deviation of the nth pulse relative to the first pulse in the filter output of the other receiving nodes respectively.

[0048] S22. Based on the time deviation, shift the output of the corresponding filter in the distance dimension to obtain the filter output after delay compensation for M receiving nodes;

[0049] S23. Perform zero-delay truncation processing on the filter output results after delay compensation of the M receiving nodes to obtain the filter output results after distance gate alignment of the M receiving nodes.

[0050] S24. Sample the filter output results after distance gate alignment of the M receiving nodes to obtain the sampling results of the received signals of the M receiving nodes, wherein the number of samples within a single pulse repetition interval is A points;

[0051] S25. Convert the sampling results of the signals received by the M receiving nodes into a fast and slow time dimension matrix.

[0052] S3. Multi-channel discrete Fourier transform is used to perform Q-point coherent accumulation of the received signals of M receiving nodes, and the RD diagram of M receiving nodes is obtained by combining the fast and slow time dimension matrix.

[0053] It should be noted that one implementation of S3 can be:

[0054] S31. Obtain the maximum unambiguous speed of the received signal to form a speed measurement range;

[0055] S32. Uniformly sample within the speed measurement range to obtain a speed measurement sequence, wherein the uniform sampling number is Q points;

[0056] S33. Based on the speed measurement sequence, define row vectors to obtain the transformation matrices corresponding to the M receiving nodes;

[0057] S34. Based on the fast and slow time dimension matrices corresponding to the M receiving nodes and the transformation matrix, the RD diagram of the M receiving nodes is obtained.

[0058] Based on this, coherent accumulation within the receiving node is performed on the pulse compression result after interference suppression, which can highlight the target's range and velocity information while suppressing interference.

[0059] S4. Perform P-point coherent accumulation between the M receiving nodes using Fast Fourier Transform to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

[0060] It should be noted that one implementation of S4 can be:

[0061] S41. Based on the RD diagram of the M receiving nodes, form A three-dimensional matrix;

[0062] S42, regarding the above The three-dimensional matrix is ​​subjected to a P-point fast Fourier transform along the M-dimensional plane to obtain the fast Fourier transform result.

[0063] S43. Flatten the Fast Fourier Transform result along the distance dimension to obtain... A two-dimensional matrix;

[0064] S44. Take the horizontal and vertical coordinates corresponding to the maximum value of the two-dimensional matrix to obtain the distance and speed of the target.

[0065] Based on this, performing coherent accumulation between receiving nodes again on the coherent accumulation results within the receiving node can further improve the signal-to-noise ratio.

[0066] Furthermore, prior to S1, it also includes:

[0067] The transmitted signals from the M transmitting nodes of the radar system are spliced ​​together in the time domain to form a continuous signal, which is then received by the M receiving nodes of the radar system.

[0068] This ensures the orthogonality of each transmitted signal in the frequency domain.

[0069] Furthermore, prior to S1, it also includes:

[0070] S01. Based on the carrier frequencies of the transmitted signals from the M transmitting nodes of the radar system, the received signals from the M receiving nodes are down-converted and bandpass filtered respectively to obtain the bandpass filtering results.

[0071] S02. Based on the M transmitting nodes of the radar system, design the corresponding matched filter;

[0072] S03. Apply the matched filters corresponding to the M transmitting nodes to the bandpass filtering result to obtain the matched filtering processing result of the M receiving nodes.

[0073] Based on this, by performing down-conversion and bandpass filtering on the received signal, some interference and most noise can be effectively filtered out.

[0074] In summary, this method proposes a multi-base radar cooperative transmission processing technique to combat intermittent sampling interference (ISS). It considers that each radar node transmits a pulse signal with a different time width and orthogonal frequency domain, which are then spliced ​​together in the time domain to form a continuous signal. Due to the characteristics of ISS, the jammer can intercept a portion of the target signal. By utilizing the multi-pulse structure, the interception length of a single transmitted signal can be reduced, thereby decreasing the interference level on individual transmitted signals. Then, the partial interception characteristic of the jammer is utilized to filter out the interference during matched filtering. Furthermore, subsequent coherent accumulation within a single radar node and coherent accumulation between multiple radar nodes further highlight the range and velocity information of the real target. This method effectively suppresses ISS without requiring prior knowledge of the interference.

[0075] Example 2

[0076] This embodiment provides the specific implementation steps of another method for combating multi-main-lobe intermittent sampling interference through multi-radar signal coordination, as follows:

[0077] Step 1: Transmit radar signal.

[0078] Assuming the radar system has There are [number] radar transmitting nodes, each transmitting a pulse with a width of [value]. The signal has a pulse repetition interval (PRI) of . The coherent processing interval (CPI) is In a CPI One PRI. Therefore, the above parameters can be expressed as:

[0079]

[0080] No. The transmission sequence of a number of transmission pulses can be represented as:

[0081]

[0082] in, To represent an imaginary number, we have = , The width is indicated as bandwidth is Linear Frequency Modulation (LFM) signal. For carrier frequency, For the first The frequency offset of each transmitted signal. To ensure the orthogonality of each transmitted signal in the frequency domain, we have... , The frequency spacing of the transmitted signal. Through The samples were obtained by sampling without replacement.

[0083] Finally, a continuous signal formed by splicing multiple pulse signals can be represented as:

[0084]

[0085] in, Indicates the first Without loss of generality, the transmission time of each transmitted signal, , , For the first The duration of each sub-pulse t represents time.

[0086] Step 2: Obtain the echo signal.

[0087] Consider the following scenario: there exists a point target in the airspace equipped with a self-defense jammer. Then, for the ... The target echo received by a receiving node can be written as:

[0088]

[0089] Considering the target as a distant target, its position and velocity relative to each receiving node can be regarded as uniform. Therefore, the target echo can be written as:

[0090]

[0091] in, These represent the target's distance and radial velocity relative to the radar system, respectively. This indicates the impact of target reflectivity and channel propagation on the signal. It represents the speed of light.

[0092] Depending on the forwarding strategy, Interrupted Sampling Jamming (ISJ) can be divided into three categories: Interrupted Sampling Repeater Jamming (ISRJ), Interrupted Sampling Cycling Jamming (ISCJ), and Interrupted Sampling Direct Jamming (ISDJ). Considering the sampling duration of the jammer during radar signal transmission is... The sampling period is The specific type of interference will be randomly selected from ISRJ, ISCJ, and ISDJ. The signal intercepted by the interference can then be represented as:

[0093]

[0094] in, Specifically, the interception strategy for the jammer can be expressed as:

[0095]

[0096] in, Represents a rectangular impulse function, when The value is . Represents the impulse function. Let be the number of interceptions. Therefore, the total interference signal can be expressed as:

[0097]

[0098] in, For the number of reposts, For the first The start time of the next relay. Since this jamming is self-defense jamming, the jammer's range and radial velocity are assumed to be consistent with the target. Therefore, the jamming signal received by the radar system can be expressed as:

[0099]

[0100] in, This represents the impact of target reflectivity and channel propagation on the signal. Therefore, the total received signal of the radar system can be expressed as:

[0101]

[0102] in, The mean is The variance is Gaussian white noise.

[0103] Step 3: Signal processing.

[0104] Step 3-1: Multi-channel pulse compression.

[0105] Based on the different carrier frequencies of the signals transmitted by each receiving node, the following are respectively... The received signals of each receiving node are processed. The downconversion and bandpass filtering yield the following results:

[0106]

[0107] in, They represent the first The target signal, interference signal, and noise at each node after down-conversion and bandpass filtering. For the first The transmission signal of the node. After this step, other nodes that are not the first... The signals transmitted by each node, the interference signals intercepted from these transmitted signals, and most of the noise are filtered out.

[0108] based on With different transmit nodes, the following filters can be designed. ,in This represents the conjugate operation. Since the pulse width of each pulse is narrow, the Doppler frequency shift caused by the time difference within the pulse is negligible. The first... Each transmitting node corresponds to a filter that acts on... The obtained pulse compression result can be written as:

[0109]

[0110] For a specific time Pulse compression results It can be written as:

[0111]

[0112] Assuming the time delay corresponding to the actual target location is The time delay corresponding to the false targets formed by interference is To suppress interference, consider the following formula.

[0113]

[0114] in, It can be seen as The expansion. Regarding the dimensions obtained from the expansion. This is called the matching dimension. Next, we will identify and separate interference based on the matching dimension.

[0115] Assume the received target signal power is The power of the interference signal is .when That is, when the real target and the false target do not overlap, the time delay corresponding to the false target. Place, The expansion of the matching dimension only has amplitude in some regions, while the amplitude in other regions is 0; the actual target corresponds to the time delay. Place, In all matching dimensions Both have amplitude values. These differences are used to distinguish between real and false targets, and the location of the false target is determined. Set to zero.

[0116] When the interference and the target coincide, the corresponding time delay In the expansion of the matching dimension, it can be divided into two parts: only the target exists. Its amplitude is constant; the target and the interference exist simultaneously. Its amplitude will oscillate within a certain range:

[0117]

[0118] The time delay corresponding to the overlap of target and interference The summation of the magnitudes along the unfolded dimension is divided by the length of the unfolded dimension to calculate the result. The amplitude of the signal is considered as the target signal if it is less than the mean, and if it is greater than the mean, it is considered as the target signal plus interference signal and is set to zero.

[0119] After performing interference suppression operations on the matched dimension, the processed... along Summing the dimensions yields the pulse compression result. The pulse compression results are as follows:

[0120]

[0121] in, This indicates that after interference suppression processing, the first... The pulse and the first The complex envelope of the output of a matched filter. and These are interference output and noise output, respectively.

[0122] Step 3-2: Align the distance to the gate.

[0123] Based on the output of the first receiving node filter and the known durations of each transmitted signal pulse, the... The output of the filter at the receiving node is the first Each pulse has a time deviation relative to its first pulse output. The corresponding filter output is shifted along the distance dimension to compensate for these delays and to truncate the portion of the signal that exceeds zero delay. The shifted result after zero-delay truncation is shown below. It can be represented as:

[0124]

[0125] Because a CPI contains pulses, and PRT is Therefore, the sampled results can be transformed into a fast and slow time dimension matrix. ,in For each The number of sampling points.

[0126] Step 3-3: Receiver node internal coherence accumulation:

[0127] The received signals from each receiving node are accumulated using a multi-channel discrete Fourier transform (MC-DFT). Assume the maximum unambiguous speed of this signal is... Within the speed measurement range Uniform sampling Points were used to obtain the speed measurement sequence. ,in, , Define the following row vector:

[0128]

[0129] Able to obtain the first The transformation matrix corresponding to the receiving node is So, the first... Each receiving node receives a signal corresponding to The MC-DFT process can be represented as:

[0130]

[0131] in, That is, the first RD (Range-Doppler) diagram of each receiving node.

[0132] Steps 3-4: Receive the coherent accumulation between nodes.

[0133] get After the RD diagram of each receiving node is formed, a A three-dimensional matrix, along the third dimension The FFT transformation of the points yields a length of After obtaining the FFT transform result, it is tiled along the distance dimension to achieve coherent accumulation between receiving nodes and high-precision ranging. Ultimately, a... Two-dimensional matrix , The x and y coordinates corresponding to the maximum values ​​are the distance and velocity of the real target.

[0134] This embodiment further includes simulation verification and analysis, including: cooperative transmission and reception resisting single intermittent sampling interference and cooperative transmission and reception resisting multiple intermittent sampling interference, as detailed below:

[0135] Simulation 1: Cooperative transmit and receive to resist single intermittent sampling interference

[0136] Simulation parameters: Target distance and velocity are set to 100km and 150m / s respectively. Radar parameters are set as follows: Radar carrier frequency is... signal bandwidth signal pulse time The number of repetitive pulses within CPI is Single transmitted signal pulse width range Inter-frequency spacing of transmitted signals Transmitted signal bandwidth Receiver signal-to-noise ratio Receiver interference-to-noise ratio Simultaneously with time width ,bandwidth The carrier frequency is The signal was compared with a standard LFM signal. The enemy jammer's jamming parameters were set as follows: jamming type ISRJ, jamming sampling duration... Interference sampling period .

[0137] Simulation analysis: From the attached Figure 2 It can be seen that the signals transmitted by multiple radar transmitting nodes are spliced ​​into a continuous signal in the time domain, and the frequencies of each transmitted signal are orthogonal to each other.

[0138] From the appendix Figure 3 (a) It can be seen that, in the case of transmitting coordinated signals, each receiving node can directly filter out most of the interference while performing pulse compression using the proposed interference suppression method; from the attached... Figure 3 (b) It can be seen that when transmitting traditional LFM signals, the matched filtering results are greatly affected by interference signals.

[0139] From the appendix Figure 4 (a) Appendix Figure 4 (b) Appendix Figure 4 (c) Appendix Figure 4 (d) It can be seen that by performing coherent accumulation within sub-pulse on the pulse compression result after interference suppression, the target's distance and velocity information can be highlighted while suppressing interference.

[0140] From the appendix Figure 5 (a) shows that performing coherent accumulation between receiving nodes on the results of coherent accumulation within the receiving node further improves the signal-to-noise ratio. This figure indicates the presence of a point target at 100km and 150.32m / s, consistent with the simulation parameters, thus verifying the effectiveness of the proposed multi-radar signal coordination technique for combating multi-main-lobe intermittent sampling interference. (See attached figure...) Figure 5 (b) It can be seen that the target position cannot be correctly obtained when transmitting traditional LFM signals.

[0141] Simulation 2: Cooperative Transmitter-Receiver Anti-interference from Multiple Intermittent Sampling Interferences

[0142] Simulation parameters: Target distance and velocity are set to 160km and 150m / s respectively. Radar parameters are set as follows: Radar carrier frequency is... signal bandwidth signal pulse time The number of repetitive pulses within CPI is Single transmitted signal pulse width range Inter-frequency spacing of transmitted signals Transmitted signal bandwidth Receiver signal-to-noise ratio Receiver interference-to-noise ratio Simultaneously with time width ,bandwidth The carrier frequency is The signal is compared with a standard LFM signal. Considering the opposing side has three jammers, each operating independently, and each jammer randomly selects one of three jamming signal patterns: ISRJ, ISCJ, or ISDJ. The enemy jammer's jamming parameters are set as follows: jamming sampling time is... Randomly selected from among them, the interference sampling period is within Choose randomly from among them.

[0143] Simulation analysis: From the attached Figure 6 It can be seen that the signals transmitted by multiple radar transmitting nodes are spliced ​​into a continuous signal in the time domain, and the frequencies of each transmitted signal are orthogonal to each other.

[0144] From the appendix Figure 7 (a) It can be seen that, under the condition of transmitting coordinated signals, each receiving node can directly filter out most of the interference while performing pulse compression using the proposed interference suppression method. Furthermore, because the transmission duration of the fourth radar node is relatively short, the remaining target signal after interference removal is short and cannot accumulate a high peak value; from the appendix... Figure 7 (b) It can be seen that when transmitting traditional LFM signals, the matched filtering results are greatly affected by interference signals.

[0145] From the appendix Figure 8 (a) Appendix Figure 8 (b) Appendix Figure 8 (c) shows that performing coherent accumulation within sub-pulses on the pulse compression result after interference suppression processing can highlight the target's range and velocity information while suppressing interference. (From the appendix...) Figure 8 (d) It can be seen that the transmission duration of the fourth radar node is relatively short, and after eliminating interference, it is impossible to accumulate a high peak value.

[0146] From the appendix Figure 9 (a) shows that performing coherent accumulation between receiving nodes on the results of coherent accumulation within the receiving node further improves the signal-to-noise ratio. This figure indicates the presence of a point target at 160km and 150.32m / s, consistent with the simulation parameters, thus verifying the effectiveness of the proposed multi-radar signal coordination technique for combating multi-main-lobe intermittent sampling interference. (See attached figure...) Figure 9 (b) It can be seen that the target position cannot be correctly obtained when transmitting traditional LFM signals.

[0147] Example 3

[0148] This embodiment provides a multi-radar signal coordinated anti-multi-main-lobe intermittent sampling interference device. The device specifically includes:

[0149] The pulse compression module is used to perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by M receiving nodes of the radar system, and to perform interference suppression processing along the expanded dimension to obtain the filter output results of M receiving nodes.

[0150] The distance gate alignment module is used to perform distance gate alignment processing on the filter output results of the M receiving nodes and then sample them, and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A.

[0151] The first coherent accumulation module is used to perform Q-point coherent accumulation of the received signals of M receiving nodes using multi-channel discrete Fourier transform, and to obtain the RD diagram of M receiving nodes by combining the fast and slow time dimension matrix.

[0152] The second coherent accumulation module is used to perform P-point coherent accumulation between the M receiving nodes using a fast Fourier transform on the RD graphs of the receiving nodes, to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

[0153] Preferably, the device further includes a signal splicing module, specifically used for:

[0154] The transmitted signals from M transmitting nodes of the radar system are spliced ​​together in the time domain to form a continuous signal.

[0155] This ensures the orthogonality of each transmitted signal in the frequency domain.

[0156] Preferably, the device further includes a bandpass filter module, specifically used for:

[0157] Based on the carrier frequencies of the transmitted signals from the M transmitting nodes of the radar system, the received signals from the M receiving nodes are down-converted and bandpass filtered respectively to obtain the bandpass filtering results.

[0158] Design a corresponding matched filter based on M transmitting nodes of a radar system;

[0159] The matched filters corresponding to the M transmitting nodes are applied to the bandpass filtering result to obtain the matched filtering processing result for the M receiving nodes.

[0160] Based on this, by performing down-conversion and bandpass filtering on the received signal, some interference and most noise can be effectively filtered out.

[0161] In summary, this device proposes a multi-base radar-based cooperative transmission processing technique to combat intermittent sampling interference. It considers that each radar node transmits a pulse signal with a different time width and orthogonal frequency domain, which are then spliced ​​together in the time domain to form a continuous signal. Due to the characteristics of intermittent sampling interference, the jammer will intercept a portion of the target signal. By utilizing the multi-pulse structure, the interception length of a single transmitted signal can be reduced, thereby decreasing the interference level on individual transmitted signals. Then, by utilizing the partial interception characteristic of the jammer, the interference is filtered out during matched filtering. Furthermore, subsequent coherent accumulation within a single radar node and coherent accumulation between multiple radar nodes further highlight the range and velocity information of the true target. This achieves effective suppression of intermittent sampling interference without requiring prior knowledge of the interference.

[0162] Example 4

[0163] In another feasible embodiment, this embodiment provides a device for coordinating multiple radar signals to resist intermittent sampling interference of multiple main lobes, the device specifically including:

[0164] A processor; and a memory for storing computer-executable instructions, which, when executed, cause the processor to perform the steps as described in any of the above method embodiments.

[0165] Example 5

[0166] In another feasible embodiment, this embodiment provides a storage medium for multi-radar signal coordination to resist multi-main-lobe intermittent sampling interference, the storage medium specifically including:

[0167] The storage medium stores a processing program for multi-radar signal cooperative anti-multi-main-lobe intermittent sampling interference. When the processor executes the multi-radar signal cooperative anti-multi-main-lobe intermittent sampling interference processing program, it implements the steps as described in any of the above method embodiments.

[0168] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of this application should be included within the scope of the claims of this application.

Claims

1. A method for combating multi-main-lobe intermittent sampling interference through multi-radar signal coordination, characterized in that, include: S1. Perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by the M receiving nodes of the radar system, and perform interference suppression processing along the expanded dimension to obtain the filter output results of the M receiving nodes. S2. After performing range gate alignment processing on the filter output results of the M receiving nodes, sample the results and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A. S3. Multi-channel discrete Fourier transform is used to perform Q-point coherent accumulation of the received signals of M receiving nodes, and the RD diagram of M receiving nodes is obtained by combining the fast and slow time dimension matrix. S4. Perform P-point coherent accumulation between the M receiving nodes using Fast Fourier Transform to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

2. The method according to claim 1, characterized in that, Before S1, it also includes: The transmitted signals from the M transmitting nodes of the radar system are spliced ​​together in the time domain to form a continuous signal, which is then received by the M receiving nodes of the radar system.

3. The method according to claim 1, characterized in that, Before S1, it also includes: S01. Based on the carrier frequencies of the transmitted signals from the M transmitting nodes of the radar system, the received signals from the M receiving nodes are down-converted and bandpass filtered respectively to obtain the bandpass filtering results. S02. Based on the M transmitting nodes of the radar system, design the corresponding matched filter; S03. Apply the matched filters corresponding to the M transmitting nodes of the radar system to the bandpass filtering result to obtain the matched filtering processing result of the M receiving nodes.

4. The method according to claim 1, characterized in that, S1 includes: S11. Expand the summation or integration process of the matched filtering results of the signals received by the M receiving nodes of the radar system in a dimensional manner to obtain the two-dimensional matched filtering results of the signals received by the M receiving nodes. S12. Iterate through the two-dimensional matched filtering results of the received signals of M receiving nodes along the time delay. Determine the time delay corresponding to the target, the time delay corresponding to the interference, and the time delay corresponding to the target plus interference based on the amplitude of the two-dimensional matched filtering results in the unfolded dimension. Set the two-dimensional matched filtering results at the time delay corresponding to the interference and the time delay corresponding to the target plus interference to 0 to obtain the two-dimensional matched filtering results after interference suppression. S13. The two-dimensional matched filtering result after interference suppression is summed along the unfolded dimension to obtain the filter output results of M receiving nodes.

5. The method according to claim 4, characterized in that, The step of determining the time delay corresponding to the target, the time delay corresponding to the interference, and the time delay corresponding to the target plus interference based on the magnitude of the two-dimensional matched filtering result in the unfolded dimension includes: S12-1. Determine whether the two-dimensional matched filtering result at the current time delay has an amplitude in the unfolded dimension; S12-2. If all values ​​have amplitude, then determine that the current time delay is the time delay corresponding to the target. If not all values ​​have amplitude, then determine whether the two-dimensional matched filtering result at the current time delay has amplitude in only some regions in the unfolded dimension, and whether the amplitude in other regions is close to 0. S12-3. If yes, then determine that the current delay is the delay corresponding to the interference; if no, then determine that the current delay is the delay corresponding to the overlap of the target and the interference. S12-4. Sequentially determine whether the amplitude of the two-dimensional matched filtering result at the time delay corresponding to the overlap of the target and the interference is greater than the average amplitude at that time delay; S12-5. If the current delay is greater than the average amplitude, then the current delay is determined to be the delay corresponding to the target plus interference. If the current delay is less than the average amplitude, then the current delay is determined to be the delay corresponding to the target.

6. The method according to claim 5, characterized in that, Before S12-4, it also includes: The mean amplitude at the time delay corresponding to the overlap of the target and the interference is obtained by summing the amplitudes of the two-dimensional matched filtering results in the unfolded dimension and dividing by the length of the unfolded dimension.

7. The method according to claim 1, characterized in that, S2 includes: S21. Based on the filter output of the first receiving node and the known pulse duration of the transmitted signal, calculate the time deviation of the nth pulse relative to the first pulse in the filter output of the other receiving nodes respectively. S22. Based on the time deviation, shift the output of the corresponding filter in the distance dimension to obtain the filter output after delay compensation for M receiving nodes; S23. Perform zero-delay truncation processing on the filter output results after delay compensation of the M receiving nodes to obtain the filter output results after distance gate alignment of the M receiving nodes. S24. Sample the filter output results after distance gate alignment of the M receiving nodes to obtain the sampling results of the received signals of the M receiving nodes, wherein the number of samples within a single pulse repetition interval is A points; S25. Convert the sampling results of the signals received by the M receiving nodes into a fast and slow time dimension matrix.

8. The method according to claim 1, characterized in that, S3 includes: S31. Obtain the maximum unambiguous speed of the received signal to form a speed measurement range; S32. Uniformly sample within the speed measurement range to obtain a speed measurement sequence, wherein the uniform sampling number is Q points; S33. Based on the speed measurement sequence, define row vectors to obtain the transformation matrices corresponding to the M receiving nodes; S34. Based on the fast and slow time dimension matrices corresponding to the M receiving nodes and the transformation matrix, the RD diagram of the M receiving nodes is obtained.

9. The method according to claim 1, characterized in that, S4 includes: S41. Based on the RD diagram of the M receiving nodes, form A three-dimensional matrix; S42, regarding the above The three-dimensional matrix is ​​subjected to a P-point fast Fourier transform along the M-dimensional plane to obtain the fast Fourier transform result. S43. Flatten the Fast Fourier Transform result along the distance dimension to obtain... A two-dimensional matrix; S44. Take the horizontal and vertical coordinates corresponding to the maximum value of the two-dimensional matrix to obtain the distance and speed of the target.

10. A multi-radar signal coordinated anti-multi-main-lobe intermittent sampling interference device, characterized in that, include: The pulse compression module is used to perform dimensional expansion on the summation or integration process of the matched filtering results of the signals received by M receiving nodes of the radar system, and to perform interference suppression processing along the expanded dimension to obtain the filter output results of M receiving nodes. The distance gate alignment module is used to perform distance gate alignment processing on the filter output results of the M receiving nodes and then sample them, and convert the sampled results into a fast and slow time dimension matrix, where the number of sampling points is A. The first coherent accumulation module is used to perform Q-point coherent accumulation of the received signals of M receiving nodes using multi-channel discrete Fourier transform, and to obtain the RD diagram of M receiving nodes by combining the fast and slow time dimension matrix. The second coherent accumulation module is used to perform P-point coherent accumulation between the M receiving nodes using a fast Fourier transform on the RD graphs of the receiving nodes, to obtain... A two-dimensional matrix is ​​used, and the horizontal and vertical coordinates corresponding to the maximum values ​​of the two-dimensional matrix are taken as the distance and velocity of the target.

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