Multi-antenna multi-array-plane parallel anti-interference method, device and equipment and storage medium

Abstract

The invention relates to a multi-antenna multi-array-plane parallel anti-interference method, device and equipment and a storage medium, and the method comprises the steps: receiving a radio frequency signal in a space, carrying out the front-end processing of the radio frequency signal, and generating a corresponding intermediate frequency signal; parallel sampling is carried out through multiple independent sampling channels, multi-channel digital signals are generated, time sequence and symbol synchronization operation is carried out based on a parallel computing processing unit, and synchronization signals are obtained; adjusting a weighting coefficient of an antenna array surface signal to form an optimal beam; identifying and separating signals of a plurality of nodes based on the optimal beam, distinguishing each node by using an orthogonal sequence, and realizing parallel processing and interference elimination of the signals of a plurality of access nodes through cross-correlation operation; and demodulating the synchronization signal after the anti-interference processing to obtain a digital symbol, decoding the digital symbol, recovering original data, summarizing and fusing to generate a communication data packet, and outputting the communication data packet. The invention has the effect of improving the signal receiving quality.

Description

Technical Field

[0001] The present application relates to the technical field of multi-antenna technology, and in particular to a multi-antenna multi-array parallel anti-interference method, device, equipment and storage medium. Background Art

[0002] At present, with the continuous development of wireless communication technology, multi-user, multi-antenna systems have gradually become one of the key technologies to improve communication efficiency and anti-interference capabilities.

[0003] Traditional multi-antenna systems transmit and receive signals through limited antenna arrays. However, in the face of complex wireless environments and when multiple users are communicating simultaneously, the problem of signal interference becomes more prominent, resulting in reduced communication quality and slower data transmission speeds. Existing multi-antenna arrays usually use time division multiplexing or frequency division multiplexing technology to process multiple signals. This method is limited in signal processing efficiency, especially in the case of severe signal interference and channel congestion. Existing multi-antenna arrays are difficult to effectively improve signal quality and anti-interference capabilities.

[0004] The above-mentioned prior art solutions have the following defects: the existing multi-antenna array cannot effectively suppress interference signals, resulting in poor reception quality of the main signal, so there is room for improvement. Summary of the invention

[0005] In order to improve the quality of signal reception, the present application provides a multi-antenna multi-plane parallel anti-interference method, device, equipment and storage medium.

[0006] The above-mentioned invention objective of the present application is achieved through the following technical solutions: A multi-antenna multi-array parallel anti-interference method, the multi-antenna multi-array parallel anti-interference method comprising: Receive radio frequency signals in space through antenna array elements, perform front-end processing on the radio frequency signals using digital signal processing algorithms, and generate corresponding intermediate frequency signals; Performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and performing timing synchronization and symbol synchronization operations on the multi-channel digital signal based on a parallel computing processing unit to obtain a synchronization signal; Performing anti-interference processing on the synchronization signal and adjusting the weighting coefficient of the antenna array signal to form an optimal beam; Based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, and each of the nodes is distinguished by using different orthogonal sequences, and the signals of the multiple access nodes are processed in parallel and interference is eliminated by cross-correlation operation; Demodulating the synchronization signal after anti-interference processing by a demodulation algorithm to obtain digital symbols, and decoding the demodulated digital symbols based on an error correction algorithm to restore the original data information; The decoded multi-channel signals are aggregated and fused to generate a final communication data packet, and output is performed according to the communication data packet.

[0007] By adopting the above technical solution, by using antenna array elements to receive radio frequency signals and generating intermediate frequency signals through digital signal processing algorithms, complex high-frequency radio frequency signals can be effectively converted into intermediate frequency signals that are easier to process, thereby improving the processability and stability of the signal; by multi-channel independent parallel AD sampling, and timing synchronization and symbol synchronization operations on multi-channel digital signals, it is possible to ensure accurate synchronous processing of multi-channel signals, avoid interference and timing misalignment between signals, and thus ensure the integrity and reliability of signal transmission; through anti-interference processing and weighting coefficient adjustment, the interference signal is suppressed by forming an optimal beam, which can enhance the system's anti-interference ability and improve the signal reception quality; by synchronously identifying and separating the signals of multiple access nodes, and using orthogonal sequences and cross-correlation operations to eliminate interference, it is possible to achieve simultaneous access and concurrent transmission of multiple nodes, significantly improving the system's parallel processing capability and channel utilization.

[0008] In a preferred example, the present application can be further configured as follows: performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal specifically includes: The received intermediate frequency signal is sampled by multiple high-speed AD converters, and each sampling channel has an independent clock and signal path to ensure independent processing of the signals of each channel; Anti-aliasing filtering and gain adjustment are performed on the sampled data of each sampling channel to obtain the digital signal.

[0009] By adopting the above technical solution, by using multiple high-speed AD converters to sample the intermediate frequency signal, the performance of the high-speed analog-to-digital converter can be fully utilized, high-precision sampling of the signal can be ensured, and signal distortion or loss caused by low-speed sampling can be reduced; by configuring an independent clock and signal path for each sampling channel, it is ensured that the signals between the channels do not interfere with each other, and accurate signal separation and processing can be achieved; by performing anti-aliasing filtering and gain adjustment on the sampling data of each channel, high-frequency noise and aliasing in the sampling can be effectively eliminated, and at the same time, the signal intensity range can be adjusted to ensure that the signal maintains a high-quality sampling effect under different dynamic ranges, thereby improving the accuracy and reliability of signal processing.

[0010] In a preferred example, the present application can be further configured as follows: the parallel computing processing unit performs timing synchronization and symbol synchronization operations on the digital signals of multiple channels, specifically including: Perform synchronous processing of multi-channel digital signals in the time domain and frequency domain respectively to ensure that the signals of all channels are aligned in the time domain; A cyclic prefix or pilot sequence is used for symbol synchronization to ensure correct detection of symbol boundaries and improve noise immunity.

[0011] By adopting the above technical solution, by performing timing and symbol synchronization on multi-channel digital signals based on parallel computing processing units, it is possible to ensure that all channel signals are accurately aligned in the time domain, avoid time delay problems of different channel signals, and thus ensure synchronous transmission of signals; by synchronous processing of frequency domain signals, it is possible to further optimize the alignment and consistency of signal spectrum and prevent the influence of frequency offset on signal demodulation; by using cyclic prefix or pilot sequence for symbol synchronization, it is possible to ensure accurate detection of signal symbol boundaries, thereby reducing demodulation errors caused by symbol mismatch, enhancing the system's anti-interference ability in complex environments, and improving the robustness of signal processing.

[0012] In a preferred example, the present application can be further configured as follows: the anti-interference processing of the synchronization signal and the adjustment of the weighting coefficient of the antenna array signal to form an optimal beam specifically include: The optimal beamforming technology is used to suppress sidelobe interference signals, ensure the maximum gain of the mainlobe signal, and enhance the reception capability of weak signals. The synchronization signal is subjected to interference suppression based on the SMI algorithm, and the optimal beam is generated by dynamically adjusting the weighting coefficients of the antenna array.

[0013] By adopting the above technical solution and suppressing the sidelobe interference signal through the optimal beamforming technology, the interference of irrelevant signals in the receiving process can be effectively reduced, the reception quality of the mainlobe signal can be ensured, and the reception capability of weak signals can be enhanced, especially when the signal source is far away or the channel environment is complex, the signal coverage range can be improved; by suppressing the interference of the synchronization signal based on the SMI algorithm and dynamically adjusting the weighting coefficient of the antenna array, it can adapt to the dynamic interference changes in the environment and optimize the direction and strength of the beam in real time, thereby ensuring stable communication effects in an interference environment and improving the anti-interference capability of the system.

[0014] In a preferred example, the present application may be further configured as follows: the interference suppression of the synchronization signal based on the SMI algorithm and the generation of the optimal beam by dynamically adjusting the weighting coefficient of the antenna array surface specifically include: By constructing a covariance matrix of the synchronization signal, the correlation between the channels corresponding to the synchronization signals is analyzed, and the interference direction corresponding to the interference signal is identified; The optimal weighting coefficient is calculated through matrix inversion operation, the signal weight of each antenna array surface is dynamically adjusted, and the influence of the interference direction is suppressed to generate the optimal beam.

[0015] By adopting the above technical solution and constructing the covariance matrix of the synchronization signal, it is possible to analyze the correlation between the various signal channels, effectively identify the direction and characteristics of the interference signal, and thus provide a more accurate basis for subsequent signal processing; by calculating the optimal weighting coefficient through matrix inversion operation, it is possible to dynamically adjust the signal weight of each antenna array surface to ensure that the generated beam can effectively offset the signal in the interference direction, while enhancing the reception effect of the main signal, so as to flexibly respond to different interference scenarios, ensure that the system's beamforming is always in the best state, and further improve the system's anti-interference performance and signal quality.

[0016] In a preferred example, the present application may be further configured as follows: the synchronous identification and separation of signals of multiple access nodes based on the generated optimal beam specifically includes: Based on the generated optimal beam, spatially separate the signals of the multiple access nodes, and optimize the receiving path of each node signal by beamforming technology; Distinguishing signals of the plurality of access nodes based on different orthogonal sequences to achieve synchronous identification and interference separation between the nodes; The node signals after synchronous identification are processed using cross-correlation operations to ensure that multiple node signals can be demodulated simultaneously in the optimal beam environment.

[0017] By adopting the above technical solution, by synchronously identifying and separating multiple access node signals based on the generated optimal beam, it is possible to spatially distinguish the signals of different nodes, realize parallel signal processing, and avoid mutual interference of node signals; by optimizing the signal receiving path of each node through beamforming technology, it is possible to ensure that the signal of each node is in the best receiving state, thereby improving the overall efficiency of communication and the accuracy of signal processing; by using orthogonal sequences to distinguish signals, it is possible to ensure the orthogonality of the signals of each node in time and frequency, avoid signal confusion, and improve the accuracy of synchronous identification; by further processing the node signals through cross-correlation operations, it is possible to ensure that multiple node signals are demodulated simultaneously under the condition of the optimal beam, thereby improving the system's multi-node parallel processing capability.

[0018] The second object of the invention is achieved by the following technical solutions: A multi-antenna multi-array parallel anti-interference device, the multi-antenna multi-array parallel anti-interference device comprising: The RF receiving module is used to receive RF signals in space through antenna array elements, perform front-end processing on the RF signals using digital signal processing algorithms, and generate corresponding intermediate frequency signals; A parallel sampling module is used to perform parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and based on a parallel computing processing unit, perform timing synchronization and symbol synchronization operations on the multi-channel digital signal to obtain a synchronization signal; The anti-interference processing module is used to perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form an optimal beam; The signal separation module is used to synchronously identify and separate the signals of multiple access nodes based on the generated optimal beam, distinguish each node using different orthogonal sequences, and realize parallel signal processing and interference elimination of multiple access nodes through cross-correlation operations; The signal demodulation module is used to demodulate the synchronization signal after anti-interference processing through a demodulation algorithm to obtain digital symbols, and decode the demodulated digital symbols based on an error correction algorithm to restore the original data information; The data fusion module is used to aggregate and fuse the decoded multi-channel signals, generate the final communication data packet, and output according to the communication data packet.

[0019] By adopting the above technical solution, by using antenna array elements to receive radio frequency signals and generating intermediate frequency signals through digital signal processing algorithms, complex high-frequency radio frequency signals can be effectively converted into intermediate frequency signals that are easier to process, thereby improving the processability and stability of the signal; by multi-channel independent parallel AD sampling, and timing synchronization and symbol synchronization operations on multi-channel digital signals, it is possible to ensure accurate synchronous processing of multi-channel signals, avoid interference and timing misalignment between signals, and thus ensure the integrity and reliability of signal transmission; through anti-interference processing and weighting coefficient adjustment, the interference signal is suppressed by forming an optimal beam, which can enhance the system's anti-interference ability and improve the signal reception quality; by synchronously identifying and separating the signals of multiple access nodes, and using orthogonal sequences and cross-correlation operations to eliminate interference, it is possible to achieve simultaneous access and concurrent transmission of multiple nodes, significantly improving the system's parallel processing capability and channel utilization.

[0020] The third objective of the present application is achieved through the following technical solutions: A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the multi-antenna multi-array parallel anti-interference method when executing the computer program.

[0021] The fourth objective of the present application is achieved through the following technical solutions: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the multi-antenna multi-array parallel anti-interference method are implemented.

[0022] In summary, this application includes the following beneficial technical effects: 1. By using antenna array elements to receive RF signals and generating intermediate frequency signals through digital signal processing algorithms, complex high-frequency RF signals can be effectively converted into easier-to-process intermediate frequency signals, improving the processability and stability of signals; through multi-channel independent parallel AD sampling, and timing synchronization and symbol synchronization operations on multi-channel digital signals, accurate synchronous processing of multi-channel signals can be ensured, interference and timing misalignment between signals can be avoided, thereby ensuring the integrity and reliability of signal transmission; through anti-interference processing and weighting coefficient adjustment, the interference signal can be suppressed by forming an optimal beam, which can enhance the system's anti-interference ability and improve the signal reception quality; through synchronous identification and separation of signals from multiple access nodes, and interference elimination using orthogonal sequences and cross-correlation operations, multiple nodes can be connected and transmitted simultaneously, significantly improving the system's parallel processing capability and channel utilization; 2. By using multiple high-speed AD converters to sample the intermediate frequency signal, the performance of the high-speed analog-to-digital converter can be fully utilized to ensure high-precision sampling of the signal and reduce signal distortion or loss caused by low-speed sampling; by configuring independent clocks and signal paths for each sampling channel, it is ensured that the signals between channels will not interfere with each other, and accurate signal separation and processing can be achieved; by performing anti-aliasing filtering and gain adjustment on the sampling data of each channel, high-frequency noise and aliasing in the sampling can be effectively eliminated, and at the same time, the signal strength range can be adjusted to ensure that the signal maintains high-quality sampling effects under different dynamic ranges, thereby improving the accuracy and reliability of signal processing; 3. By suppressing the sidelobe interference signal through the optimal beamforming technology, the interference of irrelevant signals in the receiving process can be effectively reduced, the reception quality of the mainlobe signal can be ensured, and the reception capability of weak signals can be enhanced, especially when the signal source is far away or the channel environment is complex, the signal coverage can be improved; by suppressing the interference of the synchronization signal based on the SMI algorithm and dynamically adjusting the weighting coefficient of the antenna array, it can adapt to the dynamic interference changes in the environment and optimize the direction and strength of the beam in real time, thereby ensuring stable communication effects in an interference environment and improving the system's anti-interference capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart of a multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Figure 2This is a block diagram of a 12-channel parallel processing circuit in a multi-antenna multi-plane parallel anti-interference method in an embodiment of the present application; Figure 3 It is a schematic diagram of signal transmission and reception between a master node and a single slave node in a multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Figure 4 It is a schematic diagram of signal transmission and reception when the master node communicates with multiple slave nodes in parallel in a multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application when the slave nodes are distributed at different plane positions of the master node; Figure 5 It is a schematic diagram of signal transmission and reception when the master node communicates with multiple slave nodes in parallel in a multi-antenna multi-array parallel anti-interference method in one embodiment of the present application when the slave nodes are distributed in the same array orientation of the master node; Figure 6 is a flowchart for implementing step S20 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Figure 7 This is another implementation flow chart of step S20 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Figure 8 is a flowchart for implementing step S30 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Fig. 9 It is a synchronous correlation peak diagram after weighted merging of node 1 and node 2 in a multi-antenna multi-plane parallel anti-interference method in an embodiment of the present application; Fig.10 It is a data demodulation constellation diagram of node 1 and node 2 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Fig.11 is a flowchart for implementing step S32 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Fig.12 is a flowchart for implementing step S40 in the multi-antenna multi-plane parallel anti-interference method in one embodiment of the present application; Fig.13 This is a principle block diagram of a multi-antenna multi-array parallel anti-interference device in one embodiment of the present application; Fig.14 It is a schematic diagram of a device in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The present application is further described in detail below in conjunction with the accompanying drawings.

[0025] In one embodiment, if Figure 1 As shown, the present application discloses a multi-antenna multi-plane parallel anti-interference method, which specifically includes the following steps: S10: Receive radio frequency signals in space through antenna array elements, perform front-end processing on the radio frequency signals using digital signal processing algorithms, and generate corresponding intermediate frequency signals.

[0026] Specifically, after the RF signal is received by the antenna array element, the signal is first amplified by a low-noise amplifier (LNA) to improve the signal-to-noise ratio of the signal, so that the signal is free from noise interference during transmission and processing, and the frequency is filtered through a bandpass filter (BPF) to remove redundant frequency bands and stray signals, retaining only the signal part of the target frequency. Subsequently, the signal is input into the down-conversion circuit, and the high-frequency RF signal is converted into an intermediate frequency signal through a mixer to facilitate subsequent digital signal processing.

[0027] S20: Performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and performing timing synchronization and symbol synchronization operations on the multi-channel digital signal based on a parallel computing processing unit to obtain a synchronization signal.

[0028] Specifically, after the intermediate frequency signal is amplified and filtered, it is input into multiple independent sampling channels. Each channel is sampled in parallel through a high-speed analog-to-digital converter (ADC) to ensure the real-time and accuracy of the signal. Figure 2 As shown in the block diagram of the 12-channel parallel processing circuit, each sampling channel has an independent clock and signal path to ensure that the signals of each channel are processed independently and reduce crosstalk between signals. At the same time, during the sampling process, the system will dynamically adjust the sampling rate to adapt to changes in the signal environment and ensure that the signal sampling accuracy of different channels is consistent, providing a basis for subsequent synchronous processing.

[0029] S30: Perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form an optimal beam.

[0030] Specifically, the synchronized signal is processed for interference resistance. The system first identifies the direction and strength of the interference signal through spatial signal processing technology. Based on this information, the signal weight and phase of each array element on the antenna array are adjusted to form the optimal beam direction, pointing to the target signal source. At the same time, the phase cancellation technology is used to suppress interference signals from other directions. The formed optimal beam can concentrate on receiving the target signal and minimize the impact of the interference signal on the system.

[0031] S40: Based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, and different orthogonal sequences are used to distinguish each node, and the signals of multiple access nodes are processed in parallel and interference is eliminated through cross-correlation operation.

[0032] Specifically, based on the generated optimal beam, the signals of multiple access nodes are preliminarily synchronously identified and separated. Since the signal of each access node may come from a different spatial position, the system performs spatial processing on the received signal through beamforming technology to ensure that the signals of different access nodes are effectively separated in space, so that the signals from multiple nodes can be received at the same time without mutual interference of the signals. When processing the signal of the access node, the receiving path and beam direction can be dynamically adjusted according to the characteristics of the received signal to ensure that the signal quality is optimized. Figure 3 , Figure 4 and Figure 5 Schematic diagram of signal transmission and reception when the master node communicates with slave nodes in different spatial positions.

[0033] S50: demodulating the synchronization signal after the anti-interference processing by a demodulation algorithm to obtain digital symbols, and decoding the demodulated digital symbols based on an error correction algorithm to restore the original data information.

[0034] Specifically, the synchronization signal after anti-interference processing is demodulated. According to the modulation method used by the synchronization signal, such as QPSK, QAM, etc., the corresponding demodulation algorithm is used to process the signal to extract the original digital symbol information. In the demodulation process, not only the amplitude and phase information of the signal need to be restored, but also the noise and distortion in the channel need to be considered to ensure the accuracy of signal demodulation. After demodulation, the signal is further processed using error correction algorithms such as forward error correction (FEC) to correct bit errors caused by transmission errors and finally restore the original data information.

[0035] S60: Aggregate and fuse the decoded multi-channel signals to generate a final communication data packet, and output according to the communication data packet.

[0036] Specifically, after the demodulation and error correction processing is completed, the multi-channel decoded signals are summarized and fused. Since the signals may come from multiple channels, it is necessary to merge the signals of each channel in terms of timing and content, remove redundant information, and ensure signal integrity. The fused data packet contains all the transmission content. The system will output the data packet to the upper-level application or other communication modules for subsequent processing or display according to the specific protocol or application requirements.

[0037] In one embodiment, if Figure 2 As shown, in step S20, AD sampling is performed on the intermediate frequency signal in parallel through multiple independent sampling channels to generate a multi-channel digital signal, which specifically includes: S21: The received intermediate frequency signal is sampled through multiple high-speed AD converters. Each sampling channel has an independent clock and signal path to ensure independent processing of the signals of each channel.

[0038] Specifically, after the intermediate frequency signal enters the high-speed analog-to-digital converter (ADC), the input signal is first subjected to anti-aliasing filtering. The anti-aliasing filter eliminates the high-frequency components in the signal to prevent the high-frequency components from mixing into the low-frequency sampling signal, thereby preventing signal distortion. The filtered signal then enters the gain control module, which needs to dynamically adjust the gain value of each sampling channel based on the real-time detected signal strength to ensure that the signal will not be overloaded due to being too strong, and will not lose key data information due to being too weak. After the gain adjustment is completed, the signal is quantized into a digital signal for subsequent processing.

[0039] S22: performing anti-aliasing filtering and gain adjustment on the sampling data of each sampling channel to obtain a digital signal.

[0040] Specifically, after the intermediate frequency signal of each channel is sampled by the high-speed ADC, it undergoes further anti-aliasing processing, and the remaining high-frequency noise is accurately eliminated through a digital filter to prevent aliasing from interfering with subsequent digital processing. The filtered digital signal is input into the gain adjustment module, and the automatic gain control (AGC) function adjusts the gain level according to the dynamic range of the input signal to ensure that the signal is evenly amplified or attenuated, ultimately generating a stable and accurate multi-channel digital signal.

[0041] In one embodiment, if Figure 3 As shown, in step S20, based on the parallel computing processing unit, timing synchronization and symbol synchronization operations are performed on the digital signals of the multiple channels, specifically including: S23: Perform synchronization processing on the multi-channel digital signals in the time domain and the frequency domain respectively to ensure that the signals of all channels are aligned in the time domain.

[0042] Specifically, in the time domain synchronization process, the preset pilot sequence is used to perform timing detection on the received channel signals to identify the starting position and delay of the signal. The pilot sequence of each channel is matched with the expected reference sequence, and the time offset between channels is determined by correlation detection. Real-time adjustments are made based on these time differences so that all channel signals are aligned on the same time reference. Frequency domain synchronization detects and corrects the frequency offset of each channel by analyzing the spectral characteristics of the signal, ensuring that all channels remain consistent in the frequency domain, thereby improving synchronization accuracy.

[0043] S24: Use cyclic prefix or pilot sequence for symbol synchronization to ensure correct detection of symbol boundaries and improve noise resistance.

[0044] Specifically, during the symbol synchronization process, the starting position of the symbol is identified by detecting the cyclic prefix or pilot symbol embedded in each signal. The symbol is precisely positioned to ensure accurate detection of the symbol boundary and avoid overlap or loss between symbols. The use of pilot symbols improves the system's anti-interference capability. In the presence of noise interference, multiple correlation detections can be used to eliminate the impact of high-frequency noise on symbol synchronization, thereby ensuring the accuracy of subsequent demodulation operations.

[0045] In one embodiment, if Figure 4 As shown, in step S10, anti-interference processing is performed on the synchronization signal, and the weighting coefficient of the antenna array signal is adjusted to form an optimal beam, which specifically includes: S31: Suppress sidelobe interference signals through optimal beamforming technology, ensure maximum gain of mainlobe signals, and enhance the reception capability of weak signals.

[0046] Specifically, the signal direction received by each antenna array is analyzed, and the main interference direction is identified by calculating the signal arrival angle. Then, based on the analysis results, beamforming technology is used to dynamically adjust the phase and amplitude of each antenna array element to generate an optimal beam pointing to the desired target signal direction, maximizing the reception of the main signal while effectively suppressing interference signals from side lobes and other directions, thereby ensuring the quality and integrity of the received signal.

[0047] S32: Suppress the interference of synchronization signals based on the SMI algorithm and generate the optimal beam by dynamically adjusting the weighting coefficients of the antenna array.

[0048] Specifically, based on the SMI algorithm, the system performs interference suppression on the synchronized signal and optimizes signal reception by adjusting the weighting coefficient of the antenna array signal, such as Fig. 9 The synchronous correlation peak diagram after the weighted combination of node 1 and node 2 is shown. In this process, the weights of the antenna array elements are dynamically adjusted according to the characteristics of the received signal to generate the optimal beam pointing to the target signal, thereby suppressing the influence of the interference signal, such as Fig.10 The data demodulation constellation diagram of node 1 and node 2 after beam optimization is shown, so as to adaptively handle different interference environments and ensure that the main signal can still be reliably received and processed under interference conditions.

[0049] In one embodiment, if Figure 5 As shown, in step S32, interference suppression is performed on the synchronization signal based on the SMI algorithm, and the optimal beam is generated by dynamically adjusting the weighting coefficient of the antenna array, which specifically includes: S321: By constructing a covariance matrix of the synchronization signal, the correlation between the channels corresponding to the synchronization signals is analyzed, and the interference direction corresponding to the interference signal is identified.

[0050] Specifically, by constructing the covariance matrix of the synchronization signal, the correlation between each signal channel is analyzed to identify the source and direction of the interference signal. Each element of the covariance matrix represents the correlation between two signal channels. The main direction of the interference signal is identified through matrix operation. After the identification is completed, the weight of the receiving channel is adjusted according to the direction of the interference signal to ensure that the interference signal is effectively suppressed and the main signal can be received to the maximum extent, thereby ensuring the clarity and integrity of the signal.

[0051] S322: Calculate the optimal weighting coefficient through matrix inversion operation, dynamically adjust the signal weight of each antenna array, and suppress the influence of the interference direction to generate the optimal beam.

[0052] Specifically, after the covariance matrix is ​​calculated, the optimal weighting coefficients are obtained through matrix inversion operations. These weighting coefficients are used to dynamically adjust the signal weights of each antenna array to ensure that the formed receiving beam can point to the direction of the target signal. By adjusting these weight coefficients in real time, effective suppression can be performed in the direction of the interference signal, and the best reception effect of the main signal can be maintained at all times.

[0053] In one embodiment, if Figure 6 As shown, in step S40, based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, which specifically includes: S41: Based on the generated optimal beam, the signals of multiple access nodes are spatially separated, and the receiving path of each node signal is optimized through beamforming technology.

[0054] Specifically, based on the generated optimal beam, the signals of multiple access nodes are spatially separated and processed. The signal of each access node is received through beams in different directions, avoiding mutual interference among multiple signals in the same space. Beamforming technology is used to accurately adjust the direction of each beam so that the signal of each access node can be transmitted independently through different beam paths, reducing signal interference between nodes and improving the separation of received signals and signal processing efficiency.

[0055] S42: Differentiate signals of multiple access nodes based on different orthogonal sequences to achieve synchronous identification and interference separation between nodes.

[0056] Specifically, by assigning a unique orthogonal sequence, such as a Walsh code or m-sequence, to each access node, it is ensured that the signal of each node has a unique coding feature during the transmission process. The orthogonal sequence can ensure that the signals between the access nodes remain orthogonal in time and frequency to avoid signal overlap or interference. Using these orthogonal sequences, the signals of multiple nodes are distinguished at the receiving end through sequence decoding technology to ensure that the signals of each node can be correctly identified and processed.

[0057] S43: Processing the node signals after synchronization identification by cross-correlation operation to ensure that multiple node signals can be demodulated simultaneously in an optimal beam environment.

[0058] Specifically, the node signals after synchronization identification are processed using cross-correlation operations. By matching the received signals with known reference signals, the system can detect the arrival time and phase information of each node signal. The cross-correlation operation can not only accurately determine the signals of multiple nodes, but also effectively eliminate the signal interference between nodes, so that the system can demodulate the signals of multiple nodes at the same time. The demodulated signals can be further processed to ensure the efficient transmission and complete recovery of data signals.

[0059] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0060] In one embodiment, a multi-antenna multi-array parallel anti-interference device is provided, and the multi-antenna multi-array parallel anti-interference device corresponds to the multi-antenna multi-array parallel anti-interference method in the above embodiment. Figure 7 As shown, the multi-antenna multi-array parallel anti-interference device includes a radio frequency receiving module, a parallel sampling module, an anti-interference processing module, a signal separation module, a signal demodulation module, and a data fusion module. The functional modules are described in detail as follows: The RF receiving module is used to receive RF signals in space through antenna array elements, perform front-end processing on the RF signals using digital signal processing algorithms, and generate corresponding intermediate frequency signals; A parallel sampling module is used to perform parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and based on a parallel computing processing unit, perform timing synchronization and symbol synchronization operations on the multi-channel digital signal to obtain a synchronization signal; The anti-interference processing module is used to perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form an optimal beam; The signal separation module is used to synchronously identify and separate the signals of multiple access nodes based on the generated optimal beam, distinguish each node using different orthogonal sequences, and realize parallel signal processing and interference elimination of multiple access nodes through cross-correlation operations; The signal demodulation module is used to demodulate the synchronization signal after anti-interference processing through a demodulation algorithm to obtain digital symbols, and decode the demodulated digital symbols based on an error correction algorithm to restore the original data information; The data fusion module is used to aggregate and fuse the decoded multi-channel signals, generate the final communication data packet, and output according to the communication data packet.

[0061] Optional, parallel sampling modules include: High-speed sampling submodule, used to sample the received intermediate frequency signal through multiple high-speed AD converters. Each sampling channel has an independent clock and signal path to ensure independent processing of each channel signal; The signal conditioning submodule is used to perform anti-aliasing filtering and gain adjustment on the sampling data of each sampling channel to obtain a digital signal.

[0062] Optional, parallel sampling modules include: The synchronization processing submodule is used to perform synchronization processing on multi-channel digital signals in the time domain and frequency domain respectively to ensure that the signals of all channels are aligned in the time domain; The symbol synchronization submodule is used to perform symbol synchronization using a cyclic prefix or a pilot sequence to ensure correct detection of symbol boundaries and improve noise resistance.

[0063] Optionally, the anti-interference processing module specifically includes: The beamforming submodule is used to suppress sidelobe interference signals through optimal beamforming technology, ensure the maximum gain of the mainlobe signal, and enhance the reception capability of weak signals; The dynamic adjustment submodule is used to suppress interference of the synchronization signal based on the SMI algorithm and generate the optimal beam by dynamically adjusting the weighting coefficient of the antenna array.

[0064] Optionally, the dynamic adjustment submodule specifically includes: A covariance analysis unit, used to analyze the correlation between channels corresponding to each synchronization signal by constructing a covariance matrix of the synchronization signal, and identify the interference direction corresponding to the interference signal; The matrix operation unit is used to calculate the optimal weighting coefficient through matrix inversion operation, dynamically adjust the signal weight of each antenna array, suppress the influence of interference direction, and generate the optimal beam.

[0065] Optionally, the signal separation module specifically includes: The spatial separation submodule is used to perform spatial separation on the signals of multiple access nodes based on the generated optimal beam, and optimize the receiving path of each node signal through beamforming technology; A node identification submodule is used to distinguish the signals of multiple access nodes based on different orthogonal sequences to achieve synchronous identification and interference separation between the nodes; The parallel processing submodule is used to process the node signals after synchronous identification by using cross-correlation operation to ensure that multiple node signals can be demodulated simultaneously in the optimal beam environment.

[0066] For the specific definition of the multi-antenna multi-array parallel anti-interference device, please refer to the definition of the multi-antenna multi-array parallel anti-interference method above, which will not be repeated here. Each module in the above multi-antenna multi-array parallel anti-interference device can be implemented in whole or in part by software, hardware and a combination thereof. The above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0067] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a multi-antenna multi-faceted parallel anti-interference method is implemented.

[0068] 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 implements the following steps when executing the computer program: Receive the radio frequency signal in the space through the antenna array element, perform front-end processing on the radio frequency signal using the digital signal processing algorithm, and generate the corresponding intermediate frequency signal; Performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and performing timing synchronization and symbol synchronization operations on the multi-channel digital signal based on a parallel computing processing unit to obtain a synchronization signal; Perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form the optimal beam; Based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, and different orthogonal sequences are used to distinguish each node. The signals of multiple access nodes are processed in parallel and interference is eliminated through cross-correlation operations. The synchronization signal after anti-interference processing is demodulated by a demodulation algorithm to obtain digital symbols, and the demodulated digital symbols are decoded based on an error correction algorithm to restore the original data information; The decoded multi-channel signals are aggregated and fused to generate the final communication data packet, and then output according to the communication data packet.

[0069] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented: Receive the radio frequency signal in the space through the antenna array element, perform front-end processing on the radio frequency signal using the digital signal processing algorithm, and generate the corresponding intermediate frequency signal; Performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and performing timing synchronization and symbol synchronization operations on the multi-channel digital signal based on a parallel computing processing unit to obtain a synchronization signal; Perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form the optimal beam; Based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, and different orthogonal sequences are used to distinguish each node. The signals of multiple access nodes are processed in parallel and interference is eliminated through cross-correlation operations. The synchronization signal after anti-interference processing is demodulated by a demodulation algorithm to obtain digital symbols, and the demodulated digital symbols are decoded based on an error correction algorithm to restore the original data information; The decoded multi-channel signals are aggregated and fused to generate the final communication data packet, and then output according to the communication data packet.

[0070] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application 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. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0071] Those skilled in the art can clearly understand that for the convenience and simplicity of 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.

[0072] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A multi-antenna multi-array parallel anti-interference method, characterized in that: The multi-antenna multi-plane parallel anti-interference method comprises: Receive radio frequency signals in space through antenna array elements, perform front-end processing on the radio frequency signals using digital signal processing algorithms, and generate corresponding intermediate frequency signals; Performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and performing timing synchronization and symbol synchronization operations on the multi-channel digital signal based on a parallel computing processing unit to obtain a synchronization signal; Performing anti-interference processing on the synchronization signal and adjusting the weighting coefficient of the antenna array signal to form an optimal beam; Based on the generated optimal beam, the signals of multiple access nodes are synchronously identified and separated, and each of the nodes is distinguished by using different orthogonal sequences, and the signals of the multiple access nodes are processed in parallel and interference is eliminated by cross-correlation operation; Demodulating the synchronization signal after anti-interference processing by a demodulation algorithm to obtain digital symbols, and decoding the demodulated digital symbols based on an error correction algorithm to restore the original data information; The decoded multi-channel signals are aggregated and fused to generate a final communication data packet, and output is performed according to the communication data packet.

2. The multi-antenna multi-array parallel anti-interference method according to claim 1, characterized in that: The method of performing parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal specifically includes: The received intermediate frequency signal is sampled by multiple high-speed AD converters, and each sampling channel has an independent clock and signal path to ensure independent processing of the signals of each channel; Anti-aliasing filtering and gain adjustment are performed on the sampled data of each sampling channel to obtain the digital signal.

3. The multi-antenna multi-array parallel anti-interference method according to claim 1, characterized in that: The parallel computing processing unit is used to perform timing synchronization and symbol synchronization operations on the digital signals of the multiple channels, specifically including: Perform synchronous processing of multi-channel digital signals in the time domain and frequency domain respectively to ensure that the signals of all channels are aligned in the time domain; A cyclic prefix or pilot sequence is used for symbol synchronization to ensure correct detection of symbol boundaries and improve noise immunity.

4. The multi-antenna multi-array parallel anti-interference method according to claim 1, characterized in that: The anti-interference processing of the synchronization signal and the adjustment of the weighting coefficient of the antenna array signal to form an optimal beam specifically include: The optimal beamforming technology is used to suppress sidelobe interference signals, ensure the maximum gain of the mainlobe signal, and enhance the reception capability of weak signals. The synchronization signal is subjected to interference suppression based on the SMI algorithm, and the optimal beam is generated by dynamically adjusting the weighting coefficients of the antenna array.

5. The multi-antenna multi-array parallel anti-interference method according to claim 4, characterized in that: The step of suppressing interference on the synchronization signal based on the SMI algorithm and generating the optimal beam by dynamically adjusting the weighting coefficient of the antenna array specifically includes: By constructing a covariance matrix of the synchronization signal, the correlation between the channels corresponding to the synchronization signals is analyzed, and the interference direction corresponding to the interference signal is identified; The optimal weighting coefficient is calculated through matrix inversion operation, the signal weight of each antenna array surface is dynamically adjusted, and the influence of the interference direction is suppressed to generate the optimal beam.

6. The multi-antenna multi-array parallel anti-interference method according to claim 1, characterized in that: The synchronously identifying and separating signals of multiple access nodes based on the generated optimal beam specifically includes: Based on the generated optimal beam, spatially separate the signals of the multiple access nodes, and optimize the receiving path of each node signal by beamforming technology; Differentiating signals of the plurality of access nodes based on different orthogonal sequences to achieve synchronous identification and interference separation between the nodes; The node signals after synchronous identification are processed using cross-correlation operations to ensure that multiple node signals can be demodulated simultaneously in the optimal beam environment.

7. A multi-antenna multi-array parallel anti-interference device, characterized in that: The multi-antenna multi-array parallel anti-interference device comprises: The RF receiving module is used to receive the RF signal in the space through the antenna array element, perform front-end processing on the RF signal using a digital signal processing algorithm, and generate a corresponding intermediate frequency signal; A parallel sampling module is used to perform parallel AD sampling on the intermediate frequency signal through multiple independent sampling channels to generate a multi-channel digital signal, and based on a parallel computing processing unit, perform timing synchronization and symbol synchronization operations on the multi-channel digital signal to obtain a synchronization signal; An anti-interference processing module, used to perform anti-interference processing on the synchronization signal and adjust the weighting coefficient of the antenna array signal to form an optimal beam; A signal separation module, used to synchronously identify and separate the signals of multiple access nodes based on the generated optimal beam, distinguish each of the nodes using different orthogonal sequences, and realize parallel processing and interference elimination of the signals of the multiple access nodes through cross-correlation operations; A signal demodulation module is used to demodulate the synchronization signal after anti-interference processing through a demodulation algorithm to obtain digital symbols, and decode the demodulated digital symbols based on an error correction algorithm to restore the original data information; The data fusion module is used to aggregate and fuse the decoded multi-channel signals, generate a final communication data packet, and output according to the communication data packet.

8. The multi-antenna multi-array parallel anti-interference device according to claim 7, characterized in that: The parallel sampling module comprises: A high-speed sampling submodule, used for sampling the received intermediate frequency signal through multiple high-speed AD converters, each sampling channel having an independent clock and signal path to ensure independent processing of the signal of each channel; The signal adjustment submodule is used to perform anti-aliasing filtering and gain adjustment on the sampling data of each sampling channel to obtain the digital signal.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the multi-antenna multi-array parallel anti-interference method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the multi-antenna multi-array parallel anti-interference method according to any one of claims 1 to 6 are implemented.

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