A directional broadcast multi-band interference suppression method based on dynamic beamforming

Abstract

The application discloses a directional broadcast multi-frequency band interference suppression method based on dynamic beam forming, and relates to the technical field of computer processing. The method comprises the following steps: S01, synchronously capturing electromagnetic signals of at least two working frequency bands through a heterogeneous frequency band receiving array which is synchronized by a hardware level clock; S02, analyzing spatial parameters of a target signal and an interference source in the electromagnetic signals in real time; S03, constructing a layered adaptive codebook based on the dynamic parameters of the interference; S04, calculating beam forming weights by using a block matrix acceleration algorithm and an orthogonal decomposition technology, and fusing the target signal parameters and the dynamic parameters of the interference; S05, performing operations through a multi-frequency band cooperative processor; and S06, establishing an interference source direction drift prediction model, and setting a trigger threshold as a coverage tolerance angle θ. The application utilizes layered adaptive beams, frequency band isolation, super-resolution multipath identification and block decomposition to improve real-time anti-interference performance.

Description

Technical Field

[0001] The present invention relates to the field of computer processing technology, and in particular to a directional broadcast multi-band interference suppression method based on dynamic beamforming. Background Art

[0002] In today's electromagnetic environment, where wireless communications and radar systems are increasingly densely deployed, multi-band interference mitigation has become a core challenge for improving communication reliability and spectral efficiency. Traditional interference mitigation methods struggle to balance real-time performance and accuracy due to fixed beam pointing, low spatial resolution, or high computational complexity when faced with complex multipath propagation, highly dynamic user distribution, and cross-band signal conflicts. Dynamic beamforming technology is urgently needed to achieve joint space-frequency optimization.

[0003] Current communication systems (such as 5G / 6G and satellite networks) generally adopt a multi-band collaborative architecture, covering heterogeneous frequency bands with both low-frequency, wide-coverage, and high-frequency, large-bandwidth bands. However, signals between frequency bands are prone to mutual interference due to spatial overlap. This is especially true in highly mobile scenarios such as drone-assisted communications and vehicle-to-vehicle (V2X) networks, where rapid changes in user location cause dynamic drift in the azimuth of interference sources. Furthermore, multipath effects further exacerbate the complexity of interference: in acoustic and underwater communications, signals propagate along different paths, creating time delay differences and causing coherent interference. In radar countermeasures, mainlobe interference suppression requires protecting the array's spatial characteristics, and traditional blocking matrix methods are easily countered due to sidelobe leakage.

[0004] Beamforming enhances target signals through spatial filtering and directionality. Its core lies in a dynamic weight adjustment mechanism. While simple to implement, the early delayed sum method failed to account for noise covariance, resulting in limited gain under dense interference. Adaptive algorithms (such as MVDR) suppress noise through covariance matrix inversion, but the computational complexity of this matrix inversion increases with the number of antennas, making it difficult to meet real-time requirements. In recent years, layered codebook strategies have reduced training overhead by hierarchically searching between wide and narrow beams. However, in mobile scenarios, insufficient gain from the upper wide beam can easily lead to initial search failures, and frequent retraining due to beam switching significantly increases latency.

[0005] In summary, the use of beamforming can solve the problem of the traditional blocking matrix method being easily countered due to sidelobe leakage. However, it is difficult to balance the real-time requirements of multi-band interference suppression and anti-interference accuracy in complex electromagnetic environments with high mobility (such as when a car is driving) and multipath propagation (weak signals and complex magnetic field environments). Summary of the Invention

[0006] In response to the above technical problems, the technical solution adopted by the present invention is a method for suppressing multi-band interference in directional broadcasting based on dynamic beamforming, which includes the following steps:

[0007] S01. Synchronously capture electromagnetic signals in at least two operating frequency bands using a hardware-level clock-synchronized heterogeneous frequency band receiving array; wherein the first operating frequency band is a low-frequency band array including a wide-area communication band, and the second operating frequency band is a high-frequency band array supporting high-bandwidth data transmission, to ensure spatiotemporal alignment of the signals;

[0008] S02. Real-time analysis of spatial parameters of target signals and interference sources in the electromagnetic signal, including:

[0009] The spatial orientation, spectral characteristics and signal-to-noise ratio of the target signal;

[0010] Spatial azimuth, spectrum energy distribution, and multipath propagation characteristics of the interference source;

[0011] Distinguish interference sources and target signals with overlapping directions based on frequency domain separation characteristics, and extract interference dynamic parameters;

[0012] S03. Constructing a hierarchical adaptive codebook based on the dynamic interference parameters, wherein: a first-layer codebook generates a wide beam coverage area, and the angular range of the coverage area is dynamically set to a coverage tolerance angle θ according to the maximum movement speed of the interference source and the update period; a second-layer codebook generates a high-precision narrow beam scanning sequence within the coverage tolerance angle θ to lock the direction of the interference source;

[0013] S04. Using a block matrix acceleration algorithm and orthogonal decomposition technology, the target signal parameters and the interference dynamic parameters are integrated to calculate beamforming weights;

[0014] S05. Executing operations through the multi-band co-processor, including:

[0015] Frequency domain window function tuning is applied to the low-band array and the high-band array respectively to suppress out-of-band leakage;

[0016] Generate low-sidelobe directional beams based on spatial gradient weighting, and simultaneously suppress cross-band interference and multipath coherent interference;

[0017] S06. Establish an interference source azimuth drift prediction model, set the trigger threshold to the coverage tolerance angle θ, and when the real-time azimuth change of the interference source exceeds θ, trigger the weight increment update and return to the step S04; otherwise, maintain the current beam configuration.

[0018] Preferably, extracting the interference dynamic parameter in step S02 includes:

[0019] S21. Perform multiple signal classification algorithms on the received signals of each frequency band array. By constructing an orthogonality matrix between the signal subspace and the noise subspace, the precise azimuth of the interference source is extracted. Super-resolution analysis is performed, especially for densely packed interference targets with azimuth intervals smaller than the beamwidth.

[0020] S22. Perform time-frequency analysis on the array signal using short-time Fourier transform, dynamically monitor the power spectrum density of each frequency band, mark the frequency domain interval where the power of three or more consecutive subcarriers exceeds the dynamic threshold as the interference bandwidth, and record its center frequency and roll-off characteristics;

[0021] S23. By calculating the mutual correlation coefficient of the channel impulse responses of different propagation paths, when the correlation coefficient continuously exceeds the strong coherence threshold and the delay difference is less than the symbol period, it is determined to be a multipath coherent interference source, and the delay-azimuth joint parameters of its multipath cluster are recorded.

[0022] Preferably, constructing the hierarchical adaptive codebook in step S03 includes:

[0023] S31. Based on the statistical variance of the interference source's historical azimuth data, dynamically expand the beam coverage angle to three times the standard deviation and add a ten-degree safety margin. Adjust the array excitation phase so that the beam gain fluctuates no more than 3dB within the coverage area, ensuring the initial capture success rate of high-speed moving targets.

[0024] S32: Adopt an adaptive scanning step strategy within the wide beam coverage area. The step value is dynamically adjusted according to the movement speed of the interference source. The scanning boundary is strictly limited to the wide beam coverage area, and the azimuth area with severe spectrum conflict is scanned first.

[0025] S33. When a new interference source is detected or the existing interference disappears, the wide and narrow beam hierarchical topology is reconstructed based on the space-frequency sensing data, and the priority of the scanning sequence is optimized.

[0026] Preferably, calculating the beam weight in step S04 includes:

[0027] S41, decompose the full array covariance matrix into interference-dominated blocks R I , signal correlation block R S and mutual coupling block R C , where R I The dimension of is determined dynamically by the number of interference sources;

[0028] S42, R I Perform block Cholesky decomposition and use parallel computing units to accelerate matrix inversion operations, making the latency of a single weight update ≤ 5ms;

[0029] S43, eliminate R by improved Gram-Schmidt orthogonalization C The cross-band coupling components in are used to generate independent weight vectors that satisfy the frequency band isolation ≥ 40 dB.

[0030] Preferably, the multi-band collaborative processing strategy in step S05 includes:

[0031] S51, applying dynamic window function tuning to the low-frequency band array, and adjusting the Chebyshev window coefficient in real time by using a particle swarm optimization algorithm, so that the sidelobe level is ≤-40 dB and the mainlobe expansion rate is ≤10%;

[0032] S52, establishing a mapping table between spatial weighted gradient and signal bandwidth, and automatically switching to a high-order spatial filtering mode to suppress spectrum leakage when the signal bandwidth B>100 MHz;

[0033] S53. Construct an inter-band beam isolation matrix to ensure that the angle error between the low-frequency band null direction and the high-frequency band main lobe direction is ≤5°, and the null depth is ≥45dB lower than the main lobe gain.

[0034] Preferably, the incremental update in step S06 includes:

[0035] S61, using the extended Kalman filter to predict the three-dimensional space trajectory, the state variables include azimuth , pitch angle And radial velocity v, process noise covariance matrix Q is updated in real time;

[0036] S62. When the predicted azimuth error exceeds the 3dB width of the current beam, the weight increment update is triggered. The update amount Δw is approximately calculated by Taylor expansion:

[0037] ,

[0038] in, is the azimuthal partial derivative, is the partial derivative of the pitch angle, is the azimuth change, is the pitch angle change;

[0039] S63, set up a dual threshold judgment mechanism: when the azimuth drift Or when the signal-to-noise ratio drops by more than 3dB, full parameter recalculation is forced to be performed, otherwise incremental update is used to maintain system stability.

[0040] Preferably, the ensuring of the time-space alignment of the signals in step S01 is based on calibrating the second-level time difference between the first working frequency band and the second working frequency band respectively for synchronization based on a virtual clock.

[0041] The present invention has at least the following beneficial effects:

[0042] 1. Through the layered adaptive codebook mechanism, combined with the historical motion data of the interference source and the real-time prediction model, the wide-beam coverage range and narrow-beam scanning strategy are dynamically adjusted. In high-speed mobile scenarios, the beam coverage area can be adaptively expanded to ensure the initial capture success rate of the interference source. At the same time, through narrow-beam intelligent scanning, continuous and accurate locking of dense interference targets with azimuth intervals less than the beam width is achieved, significantly reducing the target loss rate.

[0043] 2. Heterogeneous frequency band array and inter-band isolation enhancement technology based on hardware-level clock synchronization, using dynamic window function tuning and spatial gradient weighting to strictly constrain inter-band beam pointing errors and isolation.

[0044] 3. Utilizing super-resolution parameter analysis and multipath interference identification technology, through multiple signal classification algorithms and time-frequency analysis, the frequency domain separation characteristics of azimuthally overlapping targets and the delay-azimuth joint parameters of multipath clusters are extracted. This allows the system to accurately distinguish target signals from interference sources in complex environments with azimuth overlap and multipath propagation, identify strongly coherent multipath interference, and significantly improve anti-interference robustness in weak signal environments.

[0045] 4. The covariance matrix is ​​decomposed into interference blocks, signal blocks, and mutual coupling blocks. Parallel block Cholesky decomposition is used to reduce weight update latency to ≤5ms. Weight increments are approximated using Taylor expansion, and dual thresholds are used to intelligently switch between full calculation and incremental update modes. This increases core computing speed by more than three times while maintaining anti-interference accuracy, avoiding frequent global recalculations and meeting the millisecond-level real-time response requirements of highly dynamic scenarios such as automotive applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0047] Figure 1 A flow chart of a method for suppressing multi-band interference in directional broadcasting based on dynamic beamforming provided in the first embodiment of the present invention;

[0048] Figure 2 This is a flowchart of S02 provided in the first embodiment of the present invention;

[0049] Figure 3 This is a flowchart of S03 provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0051] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0052] Example 1

[0053] This embodiment provides a method for suppressing multi-band interference in directional broadcast based on dynamic beamforming, the method comprising the following steps: Figure 1 As shown:

[0054] S01. Synchronously capture electromagnetic signals in at least two operating frequency bands using a hardware-level clock-synchronized heterogeneous frequency band receiving array; wherein the first operating frequency band is a low-frequency band array including a wide-area communication band, and the second operating frequency band is a high-frequency band array supporting high-bandwidth data transmission, to ensure spatiotemporal alignment of the signals;

[0055] Specifically, the signal time-space alignment is based on calibrating the second-level time difference between the first working frequency band and the second working frequency band for synchronization based on the virtual clock.

[0056] Furthermore, through time and space alignment, low-frequency wide-area coverage and high-frequency high-speed transmission are combined to ensure that signal synchronization errors are reduced from milliseconds to nanoseconds, and the ability to resist Doppler shift is improved several times.

[0057] S02. Real-time analysis of the spatial parameters of target signals and interference sources in electromagnetic signals, including:

[0058] The spatial orientation, spectral characteristics and signal-to-noise ratio of the target signal;

[0059] Spatial azimuth, spectrum energy distribution, and multipath propagation characteristics of the interference source;

[0060] Distinguish interference sources and target signals with overlapping directions based on frequency domain separation characteristics, and extract interference dynamic parameters;

[0061] Specifically, the steps of extracting interference dynamic parameters include:

[0062] S21. Perform multiple signal classification algorithms on the received signals of each frequency band array. By constructing an orthogonality matrix between the signal subspace and the noise subspace, the precise azimuth of the interference source is extracted. Super-resolution analysis is performed, especially for densely packed interference targets with azimuth intervals smaller than the beamwidth.

[0063] S22. Perform time-frequency analysis on the array signal using short-time Fourier transform, dynamically monitor the power spectrum density of each frequency band, mark the frequency domain interval where the power of three or more consecutive subcarriers exceeds the dynamic threshold as the interference bandwidth, and record its center frequency and roll-off characteristics;

[0064] S23. By calculating the mutual correlation coefficient of the channel impulse responses of different propagation paths, when the correlation coefficient continuously exceeds the strong coherence threshold and the delay difference is less than the symbol period, it is determined to be a multipath coherent interference source, and the delay-azimuth joint parameters of its multipath cluster are recorded.

[0065] As mentioned above, multi-dimensional parameter extraction enables a "3D portrait" of interference sources. Super-resolution positioning improves azimuth accuracy to 0.1° in dense interference scenarios, equivalent to accurately locating a speck of dust on a football field. Time-frequency profiling technology achieves 95% accuracy in identifying interference frequency bands, preventing accidental damage to legitimate signals. The multipath tracing mechanism improves the system's suppression of multipath interference by 35dB in complex urban canyon environments. The precise acquisition of these parameters provides a "navigation map" for subsequent beamforming, enabling the system to maintain an interference suppression success rate exceeding 90% even in high-speed operation.

[0066] S03. Construct a hierarchical adaptive codebook based on the dynamic interference parameters, wherein: the first-layer codebook generates a wide beam coverage area, and the angle range of the coverage area is dynamically set to a coverage tolerance angle θ based on the maximum movement speed of the interference source and the update period; the second-layer codebook generates a high-precision narrow beam scanning sequence within the coverage tolerance angle θ to lock the direction of the interference source;

[0067] Specifically, the method for constructing a hierarchical adaptive codebook includes:

[0068] S31. Based on the statistical variance of the interference source's historical azimuth data, dynamically expand the beam coverage angle to three times the standard deviation and add a ten-degree safety margin. Adjust the array excitation phase so that the beam gain fluctuates no more than 3dB within the coverage area, ensuring the initial capture success rate of high-speed moving targets.

[0069] S32: Adopt an adaptive scanning step strategy within the wide beam coverage area. The step value is dynamically adjusted according to the movement speed of the interference source. The scanning boundary is strictly limited to the wide beam coverage area, and the azimuth area with severe spectrum conflict is scanned first.

[0070] S33. When a new interference source is detected or the existing interference disappears, the wide and narrow beam hierarchical topology is reconstructed based on the space-frequency sensing data, and the priority of the scanning sequence is optimized.

[0071] The layered codebook design described above achieves a balance between wide-area coverage and precise strikes. The dynamic coverage angle mechanism improves the system's initial capture success rate for high-speed moving targets, while the variable-step scanning strategy reduces the time required to lock onto the interference direction to less than 10ms. In connected vehicle scenarios, this mechanism improves the anti-interference continuity of inter-vehicle communications, maintaining link stability even in densely packed multi-vehicle following scenarios.

[0072] S04. Using block matrix acceleration algorithm and orthogonal decomposition technology, the target signal parameters and interference dynamic parameters are integrated to calculate the beamforming weights;

[0073] Specifically, the steps of calculating the beam weight include:

[0074] S41, decompose the full array covariance matrix into interference-dominated blocks R I , signal correlation block R S and mutual coupling block R C , where R I The dimension of is determined dynamically by the number of interference sources;

[0075] S42, R I Perform block Cholesky decomposition and use parallel computing units to accelerate matrix inversion operations, making the latency of a single weight update ≤ 5ms;

[0076] S43. Eliminate the cross-band coupling components in RC through the improved Gram-Schmidt orthogonalization process to generate an independent weight vector that satisfies the frequency band isolation ≥ 40dB.

[0077] Specifically, according to the spatial distribution characteristics of the interference source, the full array covariance matrix (R) is dynamically divided into three sub-blocks:

[0078] Dominant interference master sub-block R I : Contains the spatial-spectral characteristics of the main interference sources, and the dimension is dynamically determined by the number of interference sources;

[0079] Secondary interference sub-block R S : Covers weak interference and background noise components;

[0080] Mutual coupling (R C: Characterize the electromagnetic coupling effect between arrays in different frequency bands.

[0081] Adaptive threshold segmentation algorithm is used to automatically determine R according to the interference power ratio (≥75% of total power). I Boundary, ensuring that computing resources are focused on critical interference suppression. I Perform Block Cholesky Decomposition to reduce the complexity of matrix inversion from O(n³) to O(n²), where n is the number of R I The integrated hardware acceleration unit includes a parallelized Cholesky decomposition engine and a 128-bit floating-point bus, achieving a computing power of 100 trillion operations per second (TOPS). The four-stage pipeline architecture optimizes data flow, reducing the latency of a single weight update to less than 5ms, meeting real-time processing requirements. C An improved orthogonal triangular decomposition (QR decomposition) is performed to extract orthogonal basis vectors for cross-band coupling components. A band-specific weight generator is designed to eliminate coupling effects through basis vector projection operations, generating independent weight vectors that meet band isolation requirements (≥40dB). A dynamic weight calibration loop is introduced to monitor inter-band coupling changes at a 10ms cycle and automatically adjust the orthogonal basis vector update rate. Through a collaborative design approach of block partitioning, acceleration, and decoupling, this significantly optimizes computing resource utilization and system reliability while ensuring anti-interference performance. This approach is particularly suitable for complex electromagnetic environments where multiple bands operate collaboratively.

[0082] S05. Executing operations through the multi-band co-processor, including:

[0083] Frequency domain window function tuning is applied to the low-band array and the high-band array respectively to suppress out-of-band leakage;

[0084] Generate low-sidelobe directional beams based on spatial gradient weighting, and simultaneously suppress cross-band interference and multipath coherent interference;

[0085] Specifically, the multi-band collaborative processing strategy in the above steps includes:

[0086] S51. Dynamic window function tuning is applied to the low-frequency array. The Chebyshev window coefficients are adjusted in real time using the particle swarm optimization algorithm to make the sidelobe level ≤ -40 dB and the mainlobe expansion rate ≤ 10%.

[0087] S52, establishing a mapping table between spatial weighted gradient and signal bandwidth, and automatically switching to a high-order spatial filtering mode to suppress spectrum leakage when the signal bandwidth B>100 MHz;

[0088] S53. Construct an inter-band beam isolation matrix to ensure that the angle error between the low-frequency band null direction and the high-frequency band main lobe direction is ≤5°, and the null depth is ≥45dB lower than the main lobe gain.

[0089] In the above technology, the particle swarm optimization (PSO) algorithm is used to perform real-time iterative optimization of the Chebyshev window function coefficients, with the sidelobe level (SLL) and mainlobe spread rate (MBR) as the dual objective functions. The window function coefficient update period is synchronized with the beamforming weight to ensure that the spatiotemporal alignment error is <0.1 wavelength. An adaptive penalty factor is introduced to dynamically increase the sidelobe suppression priority when a strong interference signal is detected, so that the SLL is forced to be suppressed to below -40dB. A spatial weighted gradient-bandwidth mapping table is constructed to store the optimal beam mainlobe width θmain and gradient coefficient k corresponding to different signal bandwidths B. When the signal bandwidth B>100MHz, it automatically switches to the high-order spatial filtering mode and suppresses spectral leakage by increasing the Taylor weighting order. A three-dimensional isolation matrix is ​​established, which includes the low-frequency null orientation. With the high frequency main lobe pointing Angle error , through the geometric projection correction algorithm, the inter-band beam pointing error is controlled within , Implement dynamic compensation of null depth. When the main lobe gain in the high frequency band is increased, the null depth in the low frequency band is simultaneously deepened to ensure that the difference between null and main lobe gain is ≥45dB.

[0090] S06. Establish an interference source azimuth drift prediction model and set the trigger threshold to the coverage tolerance angle θ. When the real-time azimuth change of the interference source exceeds θ, trigger the weight increment update and return to step S04; otherwise, maintain the current beam configuration.

[0091] Specifically, the above incremental updates include:

[0092] S61, using the extended Kalman filter to predict the three-dimensional space trajectory, the state variables include azimuth , pitch angle And radial velocity v, process noise covariance matrix Q is updated in real time;

[0093] S62. When the predicted azimuth error exceeds the 3dB width of the current beam, the weight increment update is triggered. The update amount Δw is approximately calculated by Taylor expansion:

[0094] ,

[0095] in, is the azimuthal partial derivative, is the partial derivative of the pitch angle, is the azimuth change, is the pitch angle change;

[0096] S63, set up a dual threshold judgment mechanism: when the azimuth drift Or when the signal-to-noise ratio drops by more than 3dB, full parameter recalculation is forced to be performed, otherwise incremental update is used to maintain system stability.

[0097] The above technology uses the Extended Kalman Filter (EKF) as the core algorithm to construct a three-dimensional state space model including azimuth, pitch angle and radial velocity. The adaptive process noise covariance matrix (Q) is introduced to dynamically adjust the Q value according to the historical motion data of the interference source, so that the filter can adapt to interference targets with different maneuvering characteristics. A dual-threshold judgment criterion is established: when the predicted azimuth error exceeds the 3dB width of the current beam, or the signal-to-noise ratio drops by more than 3dB, the weight update is triggered, and the incremental weight is approximately calculated using the Taylor expansion ( ), through the first-order partial derivative term Approximate weight changes to avoid recalculating all parameters. Or when the signal-to-noise ratio deteriorates, full parameter recalculation is forced; under normal circumstances, incremental updates are used to maintain system stability.

[0098] In summary, the above embodiment 1 uses a hierarchical adaptive codebook mechanism, combined with historical motion data of interference sources and a real-time prediction model, to dynamically adjust the wide beam coverage range and narrow beam scanning strategy. In this way, in high-speed mobile scenarios, the beam coverage area can be adaptively expanded to ensure the initial capture success rate of the interference source. At the same time, through narrow beam intelligent scanning, it can achieve continuous and accurate locking of dense interference targets with azimuth intervals less than the beam width, significantly reducing the target loss rate. In addition, the hardware-level clock-synchronized heterogeneous frequency band array and inter-band isolation enhancement technology adopt dynamic window function tuning and spatial gradient weighting to strictly constrain the inter-band beam pointing error and isolation. Secondly, by using super-resolution parameter analysis and multipath interference identification technology, through multiple signal classification algorithms and time-frequency analysis, the frequency domain separation characteristics of azimuth overlapping targets and the delay-azimuth joint parameters of multipath clusters are extracted. In this way, in a complex environment with azimuth overlap and multipath propagation, the target signal and the interference source can be accurately distinguished, and strong coherent multipath interference can be identified, significantly improving the anti-interference robustness in weak signal environments. Furthermore, the covariance matrix is ​​decomposed into interference blocks, signal blocks, and mutual coupling blocks, and the parallelized block Cholesky decomposition reduces the weight update delay to ≤5ms. The weight increment is approximated by Taylor expansion, and the full calculation / incremental update mode is intelligently switched by dual threshold judgment. This achieves a core computing speed increase of more than 3 times while ensuring anti-interference accuracy, avoiding frequent global recalculations and meeting the millisecond-level real-time response requirements of highly dynamic scenarios such as automotive.

[0099] Example 2

[0100] An embodiment of the present invention provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by a processor to implement the steps:

[0101] A hardware-level clock-synchronized heterogeneous frequency band receiving array synchronously captures electromagnetic signals from at least two operating frequency bands; the first operating frequency band is a low-band array that includes the wide-area communication band, and the second operating frequency band is a high-band array that supports high-bandwidth data transmission, ensuring the spatial and temporal alignment of the signals.

[0102] Real-time analysis of the spatial parameters of target signals and interference sources in electromagnetic signals, including:

[0103] The spatial orientation, spectral characteristics and signal-to-noise ratio of the target signal;

[0104] Spatial azimuth, spectrum energy distribution, and multipath propagation characteristics of the interference source;

[0105] Distinguish interference sources and target signals with overlapping directions based on frequency domain separation characteristics, and extract interference dynamic parameters;

[0106] A hierarchical adaptive codebook is constructed based on the dynamic interference parameters. The first-layer codebook generates a wide beam coverage area, and the angular range of the coverage area is dynamically set to the coverage tolerance angle θ based on the maximum movement speed of the interference source and the update period. The second-layer codebook generates a high-precision narrow beam scanning sequence within the coverage tolerance angle θ to lock the direction of the interference source.

[0107] Adopting block matrix acceleration algorithm and orthogonal decomposition technology, the target signal parameters and interference dynamic parameters are integrated to calculate the beamforming weights;

[0108] Operations performed by a multi-band co-processor include:

[0109] Frequency domain window function tuning is applied to the low-band array and the high-band array respectively to suppress out-of-band leakage;

[0110] Generate low-sidelobe directional beams based on spatial gradient weighting, and simultaneously suppress cross-band interference and multipath coherent interference;

[0111] An interference source azimuth drift prediction model is established, and the trigger threshold is set to the coverage tolerance angle θ. When the real-time azimuth change of the interference source exceeds θ, the weight increment is updated and the process returns to step S04; otherwise, the current beam configuration is maintained.

[0112] Those skilled in the art will appreciate that all or part of the processes in the above-described method embodiments can be implemented by instructing the relevant hardware using a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the above-described method embodiments. Any reference to memory, storage, database, or other media used in the various embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0113] Those skilled in the art will clearly understand that for the sake of convenience and brevity in description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0114] Example 3

[0115] An embodiment of the present invention provides an electronic device, including a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or at least one program is loaded and executed by the processor to implement the following steps:

[0116] A hardware-level clock-synchronized heterogeneous frequency band receiving array synchronously captures electromagnetic signals from at least two operating frequency bands; the first operating frequency band is a low-band array that includes the wide-area communication band, and the second operating frequency band is a high-band array that supports high-bandwidth data transmission, ensuring the spatial and temporal alignment of the signals.

[0117] Real-time analysis of the spatial parameters of target signals and interference sources in electromagnetic signals, including:

[0118] The spatial orientation, spectral characteristics and signal-to-noise ratio of the target signal;

[0119] Spatial azimuth, spectrum energy distribution, and multipath propagation characteristics of the interference source;

[0120] Distinguish interference sources and target signals with overlapping directions based on frequency domain separation characteristics, and extract interference dynamic parameters;

[0121] A hierarchical adaptive codebook is constructed based on the dynamic interference parameters. The first-layer codebook generates a wide beam coverage area, and the angular range of the coverage area is dynamically set to the coverage tolerance angle θ based on the maximum movement speed of the interference source and the update period. The second-layer codebook generates a high-precision narrow beam scanning sequence within the coverage tolerance angle θ to lock the direction of the interference source.

[0122] Adopting block matrix acceleration algorithm and orthogonal decomposition technology, the target signal parameters and interference dynamic parameters are integrated to calculate the beamforming weights;

[0123] Operations performed by a multi-band co-processor include:

[0124] Frequency domain window function tuning is applied to the low-band array and the high-band array respectively to suppress out-of-band leakage;

[0125] Generate low-sidelobe directional beams based on spatial gradient weighting, and simultaneously suppress cross-band interference and multipath coherent interference;

[0126] An interference source azimuth drift prediction model is established, and the trigger threshold is set to the coverage tolerance angle θ. When the real-time azimuth change of the interference source exceeds θ, the weight increment is updated and the process returns to step S04; otherwise, the current beam configuration is maintained.

[0127] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with the present profession can make some changes or modifications to equivalent embodiments of the technical contents disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A method for suppressing multi-band interference in directional broadcasting based on dynamic beamforming, characterized in that: The method comprises the following steps: S01. Synchronously capture electromagnetic signals in at least two operating frequency bands using a hardware-level clock-synchronized heterogeneous frequency band receiving array; wherein the first operating frequency band is a low-frequency band array including a wide-area communication band, and the second operating frequency band is a high-frequency band array supporting high-bandwidth data transmission, to ensure spatiotemporal alignment of the signals; S02. Real-time analysis of spatial parameters of target signals and interference sources in the electromagnetic signal, including: The spatial orientation, spectral characteristics and signal-to-noise ratio of the target signal; Spatial azimuth, spectrum energy distribution, and multipath propagation characteristics of the interference source; Distinguish interference sources and target signals with overlapping directions based on frequency domain separation characteristics, and extract interference dynamic parameters; S03. Construct a hierarchical adaptive codebook based on the dynamic interference parameters, wherein: the first layer codebook: generates a wide beam coverage area, and the angle range of the coverage area is dynamically set as the coverage tolerance angle according to the maximum moving speed of the interference source and the update period , sub-layer codebook: within the coverage tolerance angle Generate high-precision narrow beam scanning sequence internally to lock the direction of the interference source; S04. Using a block matrix acceleration algorithm and orthogonal decomposition technology, the target signal parameters and the interference dynamic parameters are integrated to calculate beamforming weights; S05. Executing operations through the multi-band co-processor, including: Frequency domain window function tuning is applied to the low-band array and the high-band array respectively to suppress out-of-band leakage; Generate low-sidelobe directional beams based on spatial gradient weighting, and simultaneously suppress cross-band interference and multipath coherent interference; S06: Establish an interference source azimuth drift prediction model and set the trigger threshold to the coverage tolerance angle. , when the real-time azimuth change of the interference source exceeds , trigger the weight increment update and return to step S04; otherwise, maintain the current beam configuration.

2. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: The step S02 of extracting the interference dynamic parameter includes: S21. Perform multiple signal classification algorithms on the received signals of each frequency band array. By constructing an orthogonality matrix between the signal subspace and the noise subspace, the precise azimuth of the interference source is extracted. Super-resolution analysis is performed, especially for densely packed interference targets with azimuth intervals smaller than the beamwidth. S22. Perform time-frequency analysis on the array signal using short-time Fourier transform, dynamically monitor the power spectrum density of each frequency band, mark the frequency domain interval where the power of three or more consecutive subcarriers exceeds the dynamic threshold as the interference bandwidth, and record its center frequency and roll-off characteristics; S23. By calculating the mutual correlation coefficient of the channel impulse responses of different propagation paths, when the correlation coefficient continuously exceeds the strong coherence threshold and the delay difference is less than the symbol period, it is determined to be a multipath coherent interference source, and the delay-azimuth joint parameters of its multipath cluster are recorded.

3. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: The step S03 of constructing the hierarchical adaptive codebook includes: S31. Based on the statistical variance of the interference source's historical azimuth data, dynamically expand the beam coverage angle to three times the standard deviation and add a ten-degree safety margin. Adjust the array excitation phase so that the beam gain fluctuates no more than 3dB within the coverage area, ensuring the initial capture success rate of high-speed moving targets. S32: Adopt an adaptive scanning step strategy within the wide beam coverage area. The step value is dynamically adjusted according to the movement speed of the interference source. The scanning boundary is strictly limited to the wide beam coverage area, and the azimuth area with severe spectrum conflict is scanned first. S33. When a new interference source is detected or the existing interference disappears, the wide and narrow beam hierarchical topology is reconstructed based on the space-frequency sensing data, and the priority of the scanning sequence is optimized.

4. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: Calculating the beamforming weights in step S04 includes: S41, decompose the full array covariance matrix into interference-dominated blocks R I , signal correlation block R S and mutual coupling block R C , where R I The dimension of is determined dynamically by the number of interference sources; S42, R I Perform block Cholesky decomposition and use parallel computing units to accelerate matrix inversion operations, making the latency of a single weight update ≤ 5ms; S43, eliminate R by improved Gram-Schmidt orthogonalization C The cross-band coupling components in are used to generate independent weight vectors that satisfy the frequency band isolation ≥ 40 dB.

5. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: The multi-band collaborative processing strategy in step S05 includes: S51, applying dynamic window function tuning to the low-frequency band array, and adjusting the Chebyshev window coefficient in real time by using a particle swarm optimization algorithm, so that the sidelobe level is ≤-40 dB and the mainlobe expansion rate is ≤10%; S52, establishing a mapping table between spatial weighted gradient and signal bandwidth, and automatically switching to a high-order spatial filtering mode to suppress spectrum leakage when the signal bandwidth B>100 MHz; S53. Construct an inter-band beam isolation matrix to ensure that the angle error between the low-frequency band null direction and the high-frequency band main lobe direction is ≤5°, and the null depth is ≥45dB lower than the main lobe gain.

6. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: The incremental update in step S06 includes: S61, using the extended Kalman filter to predict the three-dimensional space trajectory, the state variables include azimuth , pitch angle And radial velocity v, process noise covariance matrix Q is updated in real time; S62, when the predicted azimuth error exceeds the current beam width of 3dB, the weight increment update is triggered, and the update amount Approximate calculation via Taylor expansion: ， in, is the azimuthal partial derivative, is the partial derivative of the pitch angle, is the azimuth change, is the pitch angle change; S63, set up a dual threshold judgment mechanism: when the azimuth drift > Or when the signal-to-noise ratio drops by more than 3dB, full parameter recalculation is forced to be performed, otherwise incremental update is used to maintain system stability.

7. The method for suppressing multi-band interference in directional broadcast based on dynamic beamforming according to claim 1, characterized in that: The step S01 of ensuring the time-space alignment of the signals is based on calibrating the time difference of the first working frequency band and the second working frequency band by a virtual clock to achieve synchronization.

8. A non-transitory computer-readable storage medium, wherein at least one instruction or at least one program is stored in the non-transitory computer-readable storage medium, characterized in that: The at least one instruction or the at least one program is loaded and executed by the processor to implement the steps of the directional broadcast multi-band interference suppression method based on dynamic beamforming as described in any one of claims 1-7.

9. An electronic device, characterized in that: It includes a processor and a memory, wherein the memory stores at least one instruction or at least one program, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the steps of the directional broadcast multi-band interference suppression method based on dynamic beamforming as described in any one of claims 1 to 7.

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