A smart reflector (DISCO) jamming suppression method based on cross-site correlation differences
By constructing a cross-station covariance matrix and performing subspace decomposition, the problem of distinguishing between target echoes and interference components in a multi-station collaborative sensing integrated system is solved, achieving effective suppression of DISCO interference and improvement of target detection performance.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANJING UNIV OF SCI & TECH
- Filing Date
- 2026-03-30
- Publication Date
- 2026-06-19
AI Technical Summary
Multi-station collaborative sensing integrated systems have difficulty effectively distinguishing between target echoes and interference components, resulting in insufficient anti-interference performance, decreased accuracy in target detection and parameter estimation, and high complexity and poor real-time performance of existing methods.
Based on the cross-site correlation differences, the correlation difference features between the target scene echo and DISCO interference are extracted by constructing a cross-site covariance matrix, and then subspace decomposition and projection filtering are performed to achieve the separation and suppression of the target echo and interference components.
It effectively suppresses DISCO interference, improves target detection probability and parameter estimation accuracy, reduces system complexity, and enhances anti-interference performance and stability.
Smart Images
Figure CN122239017A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of integrated signal processing and anti-interference technology, specifically a smart reflective surface DISCO interference suppression method based on cross-site correlation differences. Background Technology
[0002] With the rapid development of wireless communication and intelligent sensing technologies, Integrated Sensing and Communication (ISAC) has become an important development direction for future intelligent transportation, unmanned systems, low-altitude economy, vehicle-to-everything (V2X) and intelligent manufacturing because it can simultaneously realize communication and sensing functions on the same hardware platform, spectrum resources and signal system. Compared with the independent operation of traditional sensing and communication systems, ISAC systems can effectively improve spectrum utilization, reduce hardware deployment costs and enhance the system's collaborative processing capabilities, showing good application prospects in complex electromagnetic environments.
[0003] In multi-station collaborative sensing and communication integration scenarios, multiple base stations can improve target detection accuracy, parameter estimation accuracy, and system robustness through spatial diversity and joint processing. However, with the development of novel electromagnetic control devices such as programmable metasurfaces and intelligent reflective surfaces, using intelligent reconfigurable surfaces (IRS) to implement DISCO interference on sensing and communication integration systems has become a new potential threat. Intelligent reflective surfaces can flexibly control the amplitude, phase, and time delay of incident signals to form highly deceptive and collaborative interference signals in space, thereby masking, distorting, or falsifying target echoes, leading to a decrease in system target detection performance, an increase in false alarm rate, and distortion of parameter estimation.
[0004] Most existing anti-jamming methods are designed for single-site scenarios, mainly relying on time-domain filtering, frequency-domain suppression, beamforming, or parameter threshold decision-making to mitigate the impact of interference. These methods have significant limitations when facing DISCO interference caused by smart reflectors. On the one hand, DISCO interference has strong spatial distribution and cross-site correlation characteristics, exhibiting a correlation structure different from the actual target echo across different base stations. On the other hand, traditional single-site processing methods struggle to fully utilize cross-site information in multi-site cooperative systems, thus making it difficult to effectively separate the target echo from the interference components. Furthermore, some existing methods rely on strong prior interference information or complex joint optimization processes, resulting in high implementation complexity, poor real-time performance, and difficulties in engineering deployment.
[0005] Therefore, a novel suppression method is urgently needed for DISCO interference caused by intelligent reflective surfaces, applicable to multi-station collaborative sensing integrated systems. This method should fully explore the correlation differences between target echoes and interference signals across different stations, effectively suppress DISCO interference without significantly increasing system complexity, and improve target detection and parameter estimation performance. Summary of the Invention
[0006] The purpose of this invention is to provide an intelligent reflective surface DISCO interference suppression method based on cross-site correlation differences, in order to solve the problems in the existing multi-site collaborative sensing integrated system that is difficult to effectively distinguish between target echoes and interference components, has insufficient anti-interference performance, and suffers from decreased accuracy in target detection and parameter estimation.
[0007] The technical solution to achieve the purpose of this invention is: a smart reflector DISCO interference suppression method based on cross-site correlation differences, the method comprising the following steps:
[0008] Step 1: Obtain the target scene echo signal of each base station in the multi-station collaborative sensing integrated system;
[0009] Step 2: Preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations;
[0010] Step 3: Establish a cross-station joint observation echo matrix based on the echo data;
[0011] Step 4: Construct the cross-station covariance matrix based on the cross-station joint observation echo matrix;
[0012] Step 5: Extract the correlation difference features between target scene echo and DISCO interference across different base stations based on the cross-site covariance matrix;
[0013] Step 6: Decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference.
[0014] Step 7: Perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo;
[0015] Step 8: Complete target detection or parameter estimation based on the reconstructed effective target echo.
[0016] Furthermore, in step 1, each base station transmits a detection signal to the target scene and receives an echo signal. The received echo signal from the target scene is represented as follows:
[0017]
[0018] In the formula, For the target scene echo signal received by the m-th base station, Let m be the target echo component received by the m-th base station at time t. Let m be the DISCO interference component induced by the smart reflector received by the m-th base station. Let M be the noise component, and M be the total number of base stations.
[0019] Furthermore, the preprocessing described in step 2 specifically includes:
[0020] Step 2-1: Perform down-conversion, filtering, and sampling processing on the target scene echo signals received by each base station to obtain the baseband echo signal;
[0021] Step 2-2: Use pilot signals to perform spatiotemporal alignment processing on each of the baseband echo signals.
[0022] Furthermore, step 3, which involves establishing a cross-site joint observation echo matrix based on the echo data, specifically includes:
[0023] Step 3-1: Extract echo samples of the same observation units after registration at each base station, and stack them in the order of the base stations to form a cross-station observation vector;
[0024] Step 3-2: Combine multiple cross-site observation vectors to construct a cross-site joint observation echo matrix to characterize the joint cross-site characteristics of target echo and DISCO interference;
[0025] The same observation unit mentioned in step 3-1 includes at least one of the same time, same distance, or same slow time unit.
[0026] Furthermore, in step 4, the diagonal elements of the cross-station covariance matrix represent the power information of the echo received by each base station, while the off-diagonal elements represent the mutual information between different base stations.
[0027] Further, the construction of the cross-station covariance matrix based on the cross-station joint observation echo matrix in step 4 is expressed as:
[0028]
[0029] In the formula, Let H represent the cross-station covariance matrix, H represent the conjugate transpose, L represent the total number of observation times, and X represent the cross-station joint observation echo matrix.
[0030] Further, in step 5, correlation difference features are extracted, specifically: by utilizing the law that the correlation terms of DISCO interference between different base stations decrease as the viewing angle difference between base stations increases, the correlation difference between the target scene echo and DISCO interference in the cross-site spatial dimension is extracted.
[0031] Step 5 specifically includes:
[0032] Step 5-1, let the target scene echo signals received by the i-th base station and the j-th base station be respectively... and The cross-correlation term of the echoes from the two base stations is expressed as: :
[0033]
[0034] In the formula, for The conjugate;
[0035] Cross-correlation terms The corresponding covariance term is represented as :
[0036]
[0037] Furthermore, the correlation terms for DISCO interference induced by the rectangular smart reflector across different base stations satisfy the following:
[0038]
[0039] In the formula, The average power of the transmitted signal. This is the first-order statistic of the complex reflection coefficient of the reflecting unit. A random variable representing the complex reflection coefficient of a reflecting unit; This is a second-order statistic of the complex reflection coefficient of a reflecting unit. For the coherent overlay term corresponding to the i-th base station, The summation of the complex exponential term of the spatial phase difference between the i-th and j-th base stations, caused by the viewing angle difference, across each reflective element of the smart reflector, is used to characterize the spatial correlation of DISCO interference between different base stations. For noise variance, The Kronecker function;
[0040] Step 5-2, define the normalized cross-correlation coefficient as... :
[0041]
[0042] when At that time, there were:
[0043]
[0044] In the formula, D is the total number of reflective units. For signal-to-noise ratio, The average power of the transmitted signal. For a rectangular smart reflective surface, the noise variance is... It is represented as the product of two directional array factors.
[0045] Furthermore, the decomposition process described in step 6 is eigenvalue decomposition, which specifically includes: selecting corresponding eigenvectors from the eigenvector matrix to form the target subspace and interference subspace respectively, based on the magnitude of the eigenvalues, energy proportions, or preset thresholds.
[0046] Furthermore, step 7 specifically includes the following processes:
[0047] Step 7-1: Construct the target projection matrix based on the target subspace. :
[0048]
[0049] Alternatively, construct an interference orthogonal complementary projection matrix based on the interference subspace. :
[0050]
[0051] In the formula, For the target subspace, Let H be the interference subspace, H denote the transpose, and I be the identity matrix;
[0052] Step 7-2: Perform projection filtering on the cross-station joint observation echo matrix using the target projection matrix or the interference orthogonal complement projection matrix to obtain:
[0053]
[0054] or,
[0055]
[0056] in, This is the echo data after interference suppression.
[0057] Furthermore, step 8, which involves performing target detection or parameter estimation based on the reconstructed effective target echo, specifically includes:
[0058] The reconstructed target effective echo is subjected to matched filtering, pulse compression, range dimension processing, slow time accumulation, Doppler processing or angle estimation processing to obtain the target detection result;
[0059] Estimate the target's distance, velocity, angle, or position parameters.
[0060] Compared with the prior art, the significant advantages of this invention are:
[0061] (1) It can effectively suppress DISCO interference caused by intelligent reflective surfaces and reduce its impact on target echo sensing and system detection performance.
[0062] (2) It can effectively distinguish between target echoes and interference components by utilizing the cross-station correlation differences in multi-station collaborative observation.
[0063] (3) In complex electromagnetic environments, it significantly improves the anti-interference performance, stability and reliability of the multi-station collaborative sensing integrated system.
[0064] (4) By using subspace projection filtering, the effective echo of the target is reconstructed while suppressing interference, thereby improving the target detection probability and the accuracy of parameter estimation.
[0065] (5) The high device sharing rate in the processing steps helps to reduce the hardware development and deployment costs in practical applications.
[0066] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description
[0067] Figure 1 This is a schematic diagram of a smart reflective surface DISCO interference suppression method based on cross-site correlation differences in one embodiment.
[0068] Figure 2 This is a schematic diagram of a multi-base station collaboration and interference scenario in one embodiment.
[0069] Figure 3 This is a schematic diagram of cross-base station echo matrix construction in one embodiment.
[0070] Figure 4 This is a schematic diagram illustrating the correlation between the target and the interference echo and the transmitted signal in one embodiment.
[0071] Figure 5 This is a schematic diagram illustrating the correlation between interference echoes and transmitted signals as a function of refresh rate in one embodiment.
[0072] Figure 6 This is a schematic diagram illustrating the improvement in the range-Doppler domain target and interference power ratio before and after interference suppression in one embodiment, where... Figure 6 (a) in the figure is the range-velocity distribution before interference suppression. Figure 6 (b) in the figure is the range-velocity distribution after interference suppression.
[0073] Figure 7 This is a schematic diagram illustrating the ratio of signal to interference power before and after interference mitigation as the refresh rate increases, in one embodiment. Detailed Implementation
[0074] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.
[0075] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.
[0076] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.
[0077] In one embodiment, a smart reflector DISCO interference suppression method based on cross-station correlation differences is provided. This method is applied to multi-station collaborative sensing integration scenarios, addressing the challenges of distinguishing between interference signals generated by smart reflectors and target echoes, and the difficulty of traditional methods in simultaneously achieving interference suppression and target preservation. By establishing a multi-station echo joint processing model, the corresponding echo matrix is constructed using the correlation differences between the target and interference in cross-station dimensional observations. By constructing the covariance matrix and performing eigenvalue decomposition to extract the target and interference subspaces, the echo signal is processed based on subspace projection, thereby achieving separation of the target echo and interference components, obtaining interference-suppressed echo data, which is then used for target detection and parameter estimation.
[0078] Combination Figure 1 The method includes the following steps:
[0079] Step 1: Obtain the target scene echo signal of each base station in the multi-station collaborative sensing integrated system;
[0080] Step 2: Preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations;
[0081] Step 3: Establish a cross-station joint observation echo matrix based on the echo data;
[0082] Step 4: Construct the cross-station covariance matrix based on the cross-station joint observation echo matrix;
[0083] Step 5: Extract the correlation difference features between target scene echo and DISCO interference across different base stations based on the cross-site covariance matrix;
[0084] Step 6: Decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference.
[0085] Step 7: Perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo;
[0086] Step 8: Complete target detection or parameter estimation based on the reconstructed effective target echo.
[0087] Furthermore, in one embodiment, in step 1, each base station transmits a detection signal to the target scene and receives an echo signal. The received target scene echo signal is represented as follows:
[0088]
[0089] In the formula, For the target scene echo signal received by the m-th base station, Let m be the target echo component received by the m-th base station at time t. Let m be the DISCO interference component induced by the smart reflector received by the m-th base station. Let M be the noise component, and M be the total number of base stations.
[0090] Furthermore, in one embodiment, the preprocessing in step 2 specifically includes:
[0091] Step 2-1: Perform down-conversion, filtering, and sampling processing on the target scene echo signals received by each base station to obtain the corresponding baseband echo signals;
[0092] Step 2-2: Use pilot signals to perform spatiotemporal alignment processing on each of the baseband echo signals to obtain synchronized and registered echo data between stations.
[0093] Furthermore, in one embodiment, step 3, establishing a cross-site joint observation echo matrix based on the echo data, specifically includes:
[0094] Step 3-1: Extract echo samples from the same observation units after registration at each base station, and stack them in the order of the base stations to form a cross-site observation vector:
[0095]
[0096] In the formula, This represents the echo sample of the m-th base station at time t;
[0097] Step 3-2: Combine the multiple cross-site observation vectors to construct a cross-site joint observation echo matrix to characterize the joint cross-site characteristics of the target echo and DISCO interference:
[0098]
[0099] In the formula, L represents the total number of observation times.
[0100] The same observation unit mentioned in step 3-1 includes at least one of the same time, same distance, or same slow time unit.
[0101] Furthermore, in one embodiment, the diagonal elements of the cross-site covariance matrix described in step 4 represent the power information of the echo received by each base station, and the off-diagonal elements represent the mutual information between different base stations.
[0102] Preferably, in some embodiments, step 4, which involves constructing the cross-station covariance matrix based on the cross-station joint observation echo matrix, is expressed as:
[0103]
[0104] In the formula, Let H represent the cross-station covariance matrix, H represent the conjugate transpose, L represent the total number of observation times, and X represent the cross-station joint observation echo matrix.
[0105] Further, in step 5, correlation difference features are extracted, specifically: by utilizing the law that the correlation terms of DISCO interference between different base stations decrease as the viewing angle difference between base stations increases, the correlation difference between the target scene echo and DISCO interference in the cross-site spatial dimension is extracted.
[0106] Step 5 specifically includes:
[0107] Step 5-1, let the target scene echo signals received by the i-th base station and the j-th base station be respectively... and The cross-correlation term of the echoes from the two base stations is expressed as: :
[0108]
[0109] In the formula, for The conjugate;
[0110] Cross-correlation terms The corresponding covariance term is represented as :
[0111]
[0112] Furthermore, the correlation terms for DISCO interference induced by the rectangular smart reflector across different base stations satisfy the following:
[0113]
[0114] In the formula, The average power of the transmitted signal. This is the first-order statistic of the complex reflection coefficient of the reflecting unit. A random variable representing the complex reflection coefficient of a reflecting unit; This is a second-order statistic of the complex reflection coefficient of a reflecting unit. For the coherent overlay term corresponding to the i-th base station, The summation of the complex exponential term of the spatial phase difference between the i-th and j-th base stations, caused by the viewing angle difference, across each reflective element of the smart reflector, is used to characterize the spatial correlation of DISCO interference between different base stations. For noise variance, The Kronecker function;
[0115] Step 5-2, define the normalized cross-correlation coefficient as... :
[0116]
[0117] when At that time, there were:
[0118]
[0119] In the formula, D is the total number of reflective units. For signal-to-noise ratio, The average power of the transmitted signal. For a rectangular smart reflective surface, the noise variance is... Represented as the product of two directional array factors, thus... It decreases as the viewing angle difference between base stations increases. Based on the above... The variation pattern was analyzed to extract the correlation differences between target echo and DISCO interference across different base stations.
[0120] Furthermore, in one embodiment, the decomposition process in step 6 is eigenvalue decomposition, specifically including: selecting corresponding eigenvectors from the eigenvector matrix to form the target subspace and interference subspace respectively, based on the magnitude of the eigenvalues, energy proportions, or preset thresholds.
[0121] Specifically:
[0122] The eigenvalue decomposition of the cross-station covariance matrix R is expressed as:
[0123]
[0124] in, U is the eigenvalue diagonal matrix, and U is the eigenvector matrix; corresponding eigenvectors are selected according to the magnitude of the eigenvalues, energy proportion, or a preset threshold to form the target subspace U. tar and interference subspace U int The target subspace is used to characterize the target echo component, and the interference subspace is used to characterize the DISCO interference component.
[0125] Furthermore, in one embodiment, step 7 specifically includes the following process:
[0126] Step 7-1: Construct the target projection matrix based on the target subspace. :
[0127]
[0128] Alternatively, construct an interference orthogonal complementary projection matrix based on the interference subspace. :
[0129]
[0130] In the formula, For the target subspace, Let H be the interference subspace, H denote the transpose, and I be the identity matrix;
[0131] Step 7-2: Perform projection filtering on the cross-station joint observation echo matrix using the target projection matrix or the interference orthogonal complement projection matrix to obtain:
[0132]
[0133] or,
[0134]
[0135] in, This is the echo data after interference suppression.
[0136] Furthermore, in one embodiment, step 8, which involves performing target detection or parameter estimation based on the reconstructed effective target echo, specifically includes:
[0137] The reconstructed target effective echo is subjected to matched filtering, pulse compression, range dimension processing, slow time accumulation, Doppler processing or angle estimation processing to obtain the target detection result;
[0138] Estimate the target's distance, velocity, angle, or position parameters.
[0139] In one embodiment, a smart reflector DISCO interference suppression system based on cross-site correlation differences is provided, the system comprising:
[0140] The first module is used to acquire the target scene echo signals of each base station in the multi-station collaborative sensing integrated system.
[0141] The second module is used to: preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations;
[0142] The third module is used to: establish a cross-station joint observation echo matrix based on the echo data;
[0143] The fourth module is used to construct the cross-station covariance matrix based on the cross-station joint observation echo matrix.
[0144] The fifth module is used to: extract the correlation difference features between target scene echo and DISCO interference at different base stations based on the cross-site covariance matrix;
[0145] The sixth module is used to: decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference;
[0146] The seventh module is used to: perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo;
[0147] The eighth module is used to achieve target detection or parameter estimation based on the reconstructed effective echo of the target.
[0148] Specific limitations regarding the intelligent reflector DISCO interference suppression system based on cross-site correlation differences can be found in the limitations of the intelligent reflector DISCO interference suppression method based on cross-site correlation differences mentioned above, and will not be repeated here. Each module in the aforementioned intelligent reflector DISCO interference suppression system based on cross-site correlation differences can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.
[0149] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements:
[0150] Step 1: Obtain the target scene echo signal of each base station in the multi-station collaborative sensing integrated system;
[0151] Step 2: Preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations;
[0152] Step 3: Establish a cross-station joint observation echo matrix based on the echo data;
[0153] Step 4: Construct the cross-station covariance matrix based on the cross-station joint observation echo matrix;
[0154] Step 5: Extract the correlation difference features between target scene echo and DISCO interference across different base stations based on the cross-site covariance matrix;
[0155] Step 6: Decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference.
[0156] Step 7: Perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo;
[0157] Step 8: Complete target detection or parameter estimation based on the reconstructed effective target echo.
[0158] For specific limitations on each step, please refer to the limitations of the intelligent reflector DISCO interference suppression method based on cross-site correlation differences mentioned above, which will not be repeated here.
[0159] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program being implemented when executed by a processor:
[0160] Step 1: Obtain the target scene echo signal of each base station in the multi-station collaborative sensing integrated system;
[0161] Step 2: Preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations;
[0162] Step 3: Establish a cross-station joint observation echo matrix based on the echo data;
[0163] Step 4: Construct the cross-station covariance matrix based on the cross-station joint observation echo matrix;
[0164] Step 5: Extract the correlation difference features between target scene echo and DISCO interference across different base stations based on the cross-site covariance matrix;
[0165] Step 6: Decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference.
[0166] Step 7: Perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo;
[0167] Step 8: Complete target detection or parameter estimation based on the reconstructed effective target echo.
[0168] For specific limitations on each step, please refer to the limitations of the intelligent reflector DISCO interference suppression method based on cross-site correlation differences mentioned above, which will not be repeated here.
[0169] As a specific example, in one embodiment, the invention will be further described with reference to the accompanying drawings.
[0170] Combination Figure 2 The system includes multiple spatially distributed base stations BS1 and BS2. i BS j and BS M The diagram includes M base stations, a target, and a smart metasurface. Each base station transmits a sensing-integrated signal and receives scene echoes. The smart metasurface modulates the reflection of the incident signal, creating interference reflection paths directed towards multiple base stations. In the diagram, the pink propagation path represents the DISCO interference propagation path induced by the smart metasurface, and the blue propagation path represents the target-related echo propagation path. R in the diagram represents the distance between the smart metasurface and the target.
[0171] Combination Figure 3 This invention establishes a cross-site joint observation echo matrix based on synchronized and registered echo data from different stations. The horizontal axis represents echo samples, and the vertical axis represents receiving base stations. Each row corresponds to an echo sample obtained by a base station at different times, and the samples in each row are stacked according to the base station order to form a cross-site observation vector. The cross-station observation vectors corresponding to multiple times are further combined to form a cross-station joint observation echo matrix. .
[0172] Combination Figure 4 The horizontal axis represents the viewing angle difference between different base stations relative to the target or smart reflector, and the vertical axis represents the magnitude of the normalized cross-correlation coefficient. The blue curve represents the theoretical correlation of the target echo, and the orange curve represents the theoretical correlation of the interference. It can be seen that the target echo maintains a high correlation across different stations, while the correlation of the DISCO interference decreases rapidly with increasing viewing angle difference, thus demonstrating the difference in correlation between the target echo and the interference across different stations.
[0173] Combination Figure 5 This diagram illustrates the interference energy distribution under different refresh rates in this invention. In the diagram, the horizontal axis represents the refresh rate (number of samples), and the vertical axis represents energy. Different colored distribution curves represent the statistical distribution of interference energy under different refresh rates. As the refresh rate changes, the distribution pattern of the interference energy changes, indicating that the DISCO interference induced by the smart reflector has different statistical characteristics at different refresh rates.
[0174] Combination Figure 6 This is a schematic diagram comparing the two-dimensional energy distribution of distance and velocity before and after interference suppression in this invention. In the figure, the horizontal axis represents distance, the vertical axis represents velocity, and the vertical axis and color bars represent normalized energy. Markers 1 and 3 correspond to the interference component, and marks 2 and 4 correspond to the target component. The inset in the upper right corner is the corresponding distance profile. Figure 6 (a) and Figure 6 As can be seen from the comparison in (b), after processing by the method of the present invention, the energy of the interference component is significantly reduced, while the target component is better preserved, thereby improving the distinguishability of target detection.
[0175] Figure 7 This diagram illustrates the relationship between the interference suppression ratio and the number of refresh samples of the intelligent reflector in this invention. The horizontal axis represents the number of refresh samples of the intelligent reflector's reflection coefficient, and the vertical axis represents the signal suppression ratio. As the number of refresh samples increases, the signal suppression ratio generally decreases and gradually stabilizes, indicating that the statistical characteristics of interference and its suppression effect are closely related to the number of refresh samples. This figure characterizes the variation of the DISCO interference suppression performance of the method of this invention under different refresh conditions.
[0176] In summary, the method of the present invention can effectively suppress DISCO interference caused by intelligent reflective surfaces, reduce the impact of such interference on target echo sensing and system detection performance, improve target detection probability, and enhance the anti-interference performance, stability, and reliability of multi-station collaborative sensing integrated system in complex electromagnetic environments.
[0177] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention without departing from its spirit and scope should be included within the protection scope of the present invention.
Claims
1. A DISCO (Differential Cross-Site Correlation) jamming suppression method based on cross-site correlation difference, characterized in that, The method includes the following steps: Step 1: Obtain the target scene echo signal of each base station in the multi-station collaborative sensing integrated system; Step 2: Preprocess the echo signals of each target scene to obtain synchronized and registered echo data between stations; Step 3: Establish a cross-station joint observation echo matrix based on the echo data; Step 4: Construct the cross-station covariance matrix based on the cross-station joint observation echo matrix; Step 5: Extract the correlation difference features between target scene echo and DISCO interference across different base stations based on the cross-site covariance matrix; Step 6: Decompose the cross-station covariance matrix to obtain the target subspace for characterizing the target echo and the interference subspace for characterizing DISCO interference. Step 7: Perform projection filtering on the echo data based on the target subspace and / or interference subspace to suppress DISCO interference and reconstruct the effective target echo; Step 8: Complete target detection or parameter estimation based on the reconstructed effective target echo.
2. The DISCO jammer rejection method based on cross-site correlation difference according to claim 1, characterized in that, In step 1, each base station transmits a detection signal to the target scene and receives the echo signal. The received echo signal from the target scene is represented as follows: wherein, is the target scene echo signal received by the mthbase station, is the target echo component received by the mthbase station at time t, is the DISCO interference component caused by the intelligent reflecting surface received by the mthbase station, is the noise component, and M is the total number of base stations.
3. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, The preprocessing described in step 2 specifically includes: Step 2-1: Perform down-conversion, filtering, and sampling processing on the target scene echo signals received by each base station to obtain the baseband echo signal; Step 2-2: Use pilot signals to perform spatiotemporal alignment processing on each of the baseband echo signals.
4. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, Step 3, establishing the cross-site joint observation echo matrix based on the echo data, specifically includes: Step 3-1: Extract echo samples of the same observation units after registration at each base station, and stack them in the order of the base stations to form a cross-station observation vector; Step 3-2: Combine multiple cross-site observation vectors to construct a cross-site joint observation echo matrix to characterize the joint cross-site characteristics of target echo and DISCO interference; The same observation unit mentioned in step 3-1 includes at least one of the same time, same distance, or same slow time unit.
5. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, In step 4, the diagonal elements of the cross-station covariance matrix represent the power information of the echo received by each base station, while the off-diagonal elements represent the mutual information between different base stations.
6. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 5, characterized in that, Step 4 describes constructing the cross-station covariance matrix based on the cross-station joint observation echo matrix, which is expressed as: In the formula, Let H represent the cross-station covariance matrix, H represent the conjugate transpose, L represent the total number of observation times, and X represent the cross-station joint observation echo matrix.
7. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, Step 5 extracts correlation difference features, specifically: using the law that the correlation terms of DISCO interference between different base stations decrease as the viewing angle difference between base stations increases, the correlation difference between the target scene echo and DISCO interference in the cross-site spatial dimension is extracted. Step 5 specifically includes: Step 5-1, let the target scene echo signals received by the i-th base station and the j-th base station be respectively... and The cross-correlation term of the echoes from the two base stations is expressed as: : In the formula, for Conjugate; Cross-correlation terms The corresponding covariance term is represented as : Furthermore, the correlation terms for DISCO interference induced by the rectangular smart reflector across different base stations satisfy the following: In the formula, The average power of the transmitted signal. This is the first-order statistic of the complex reflection coefficient of the reflecting unit. A random variable representing the complex reflection coefficient of a reflecting unit; This is a second-order statistic of the complex reflection coefficient of the reflecting unit. For the coherent overlay term corresponding to the i-th base station, The summation of the complex exponential term of the spatial phase difference between the i-th and j-th base stations, caused by the viewing angle difference, across each reflective element of the smart reflector, is used to characterize the spatial correlation of DISCO interference between different base stations. For noise variance, The Kronecker function; Step 5-2, define the normalized cross-correlation coefficient as... : when At that time, there were: In the formula, D is the total number of reflective units. For signal-to-noise ratio, The average power of the transmitted signal. For a rectangular smart reflective surface, the noise variance is... It is represented as the product of two directional array factors.
8. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, The decomposition process described in step 6 is eigenvalue decomposition, which specifically includes: selecting corresponding eigenvectors from the eigenvector matrix to form the target subspace and interference subspace respectively, based on the magnitude of the eigenvalues, energy proportions, or preset thresholds.
9. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, Step 7 includes the following specific steps: Step 7-1: Construct the target projection matrix based on the target subspace. : Alternatively, construct an interference orthogonal complementary projection matrix based on the interference subspace. : In the formula, For the target subspace, Let H be the interference subspace, H denote the transpose, and I be the identity matrix; Step 7-2: Perform projection filtering on the cross-station joint observation echo matrix using the target projection matrix or the interference orthogonal complement projection matrix to obtain: or, in, This is the echo data after interference suppression.
10. The intelligent reflector DISCO interference suppression method based on cross-site correlation differences according to claim 1, characterized in that, Step 8, which describes completing target detection or parameter estimation based on the reconstructed effective target echo, specifically includes: The reconstructed target effective echo is subjected to matched filtering, pulse compression, range dimension processing, slow time accumulation, Doppler processing or angle estimation processing to obtain the target detection result; Estimate the target's distance, velocity, angle, or position parameters.