Adaptive anti-jamming signal processing method and system based on GNSS multi-array phased array

Abstract

The present application relates to the technical field of signal processing, and especially relates to a kind of adaptive anti-interference signal processing method and system based on GNSS multi-array phased array.The method comprises the following steps: obtaining the radio frequency signal of multi-array antenna array, and adding synchronous time stamp to the radio frequency signal, and carrying out frequency conversion processing, to generate baseband signal;The baseband signal is input to signal processing unit, and the phased array processing is carried out to each array element of baseband signal, and the output is array data;The covariance information of array data is calculated, and the interference subspace is identified;The interference direction of interference subspace is determined, and the interference signal is obtained;The array output of array signal is used to suppress interference signal, and the anti-interference signal is determined;The beamforming is carried out to anti-interference signal, the satellite direction is determined, the carrier phase in this direction is tracked, and the pseudo-random code phase of anti-interference signal is determined.The present application realizes the enhancement of anti-interference ability based on signal processing technology, improves satellite signal receiving accuracy and positioning efficiency.

Description

Technical Field

[0001] This invention relates to the field of signal processing technology, and in particular to an adaptive anti-interference signal processing method and system based on a GNSS multi-element phased array. Background Technology

[0002] Traditional GNSS receivers rely heavily on single-antenna reception and fixed filtering to suppress interference. However, in complex electromagnetic environments, strong interference signals often have significantly higher power than useful satellite signals, making it difficult for single-antenna structures to provide effective spatial domain separation. Existing array antenna anti-interference methods often employ fixed beams or preset weighting schemes, lacking the ability to adaptively adjust to differences in signal-to-noise ratio (SNR) and dynamic interference environments, resulting in susceptibility to interference even under low SNR conditions. During interference identification, traditional methods often rely on energy detection or predefined thresholds, failing to accurately separate the signal subspace from the interference subspace, leading to misjudgments and impacting subsequent interference suppression. Beamforming typically relies on static direction information, lacking a joint tracking mechanism for carrier phase and pseudo-random code phase, which can cause unstable satellite signal tracking or even loss of lock. In multi-element signal processing, existing system architectures lack partitioned processing and weighted optimization mechanisms for high, medium, and low SNR signals, making it difficult to balance interference suppression capabilities with effective signal fidelity. Overall, anti-interference performance and robustness need improvement. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide an adaptive anti-interference signal processing method and system based on a GNSS multi-element phased array to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, an adaptive anti-jamming signal processing method based on a GNSS multi-element phased array is provided, applied to a GNSS receiving system. The GNSS receiving system includes a multi-element antenna array and a signal processing unit. The method includes the following steps:

[0005] Step S1: Acquire the radio frequency signal of the multi-element antenna array, add a synchronization timestamp to the radio frequency signal, and perform frequency conversion processing to generate the baseband signal;

[0006] Step S2: Input the baseband signal to the signal processing unit, perform phased array processing on each element of the baseband signal, and output array data;

[0007] Step S3: Calculate the covariance information of the array data and identify the interference subspace; determine the interference direction of the interference subspace and obtain the interference signal; use the array signal to suppress the interference signal and determine it as the anti-interference signal.

[0008] Step S4: Beamforming is performed on the anti-interference signal to determine the satellite direction, the carrier phase in that direction is tracked, and the pseudo-random code phase of the anti-interference signal is determined.

[0009] Preferably, this specification also provides an adaptive anti-jamming signal processing system based on a GNSS multi-element phased array, used to execute the adaptive anti-jamming signal processing method based on a GNSS multi-element phased array as described above. This adaptive anti-jamming signal processing based on a GNSS multi-element phased array includes:

[0010] The frequency conversion processing module is used to acquire the radio frequency signals of the multi-element antenna array, add a synchronization timestamp to the radio frequency signals, and perform frequency conversion processing to generate baseband signals;

[0011] The phased array processing module is used to input the baseband signal to the signal processing unit, perform phased array processing on each array element of the baseband signal, and output array data.

[0012] The anti-interference signal generation module is used to calculate the covariance information of the array data, identify the interference subspace, determine the interference direction of the interference subspace, obtain the interference signal, and use the array signal to suppress the interference signal of the array output, which is determined as the anti-interference signal.

[0013] The random code phase determination module is used to perform beamforming on anti-interference signals, determine the satellite direction, track the carrier phase in that direction, and determine the pseudo-random code phase of the anti-interference signal.

[0014] The beneficial effects of this invention are as follows:

[0015] (1) By introducing a multi-element phased array structure into the GNSS receiving system, combined with the synchronization timestamp and dual-stage frequency conversion processing mechanism, the unified baseband processing of multi-element radio frequency signals is realized, ensuring the time domain consistency and phase alignment of multi-channel signals, and improving the accuracy and stability of subsequent array processing.

[0016] (2) A phased array weighting strategy with signal-to-noise ratio division is adopted. Fixed weights are applied in high signal-to-noise ratio regions, minimum variance weights are applied in medium signal-to-noise ratio regions, and balanced weighting is applied in low signal-to-noise ratio regions. This achieves differentiated processing of signals of different quality, which not only improves the interference suppression capability but also maintains the fidelity of useful signals.

[0017] (3) Based on the calculation of array covariance and mutual deviation, it can accurately distinguish between signal subspace and interference subspace, realize effective identification and suppression of interference direction, break through the limitation of insufficient accuracy of traditional energy detection method, and greatly improve the robustness of anti-interference processing.

[0018] (4) By combining beamforming with carrier phase and pseudo-random code phase, the system can maintain accurate tracking of satellite direction while completing interference suppression, ensuring the continuity and stability of signal solution, and effectively improving the reliability of GNSS receiving system in complex electromagnetic environment. Attached Figure Description

[0019] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0020] Figure 1 This is a flowchart illustrating the steps of an adaptive anti-interference signal processing method based on a GNSS multi-element phased array according to the present invention.

[0021] Figure 2 This is a schematic diagram of the module flow of an adaptive anti-interference signal processing system based on a GNSS multi-element phased array in this invention.

[0022] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0023] The technical method of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0024] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0025] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0026] To achieve the above objectives, please refer to Figures 1 to 2 This invention provides an adaptive anti-jamming signal processing method based on a GNSS multi-element phased array, applied to a GNSS receiving system. The GNSS receiving system includes a multi-element antenna array and a signal processing unit. The method includes the following steps:

[0027] Step S1: Acquire the radio frequency signal of the multi-element antenna array, add a synchronization timestamp to the radio frequency signal, and perform frequency conversion processing to generate the baseband signal;

[0028] In one embodiment, the system receives radio frequency signals from a multi-element antenna array. Each element signal is sampled by a radio frequency front-end module at a sampling rate of 50MHz. At the receiving end, a high-precision synchronization module adds a timestamp to the signal to achieve nanosecond-level synchronization. Subsequently, the signal is down-converted by a local oscillator to convert the radio frequency signal into a GPS baseband signal with a center frequency of 1.575GHz, and bandpass filtering is performed to suppress noise.

[0029] In another embodiment, it is assumed that the array contains 32 array elements with a sampling rate of 60MHz, and the RF signal power of each array element is between -100dBm and -80dBm; the time synchronization module adds a timestamp with an accuracy of ±5ns to each array element; the center frequency of the down-converted baseband signal is 1.57542GHz, the filtering bandwidth is 2MHz, and 32 baseband signals are generated for subsequent processing.

[0030] Step S2: Input the baseband signal to the signal processing unit, perform phased array processing on each element of the baseband signal, and output array data;

[0031] In one embodiment, the signal processing unit performs phase correction and amplitude weighting operations on the baseband signal of each array element, calculates the phased array weights based on the array geometry information, and superimposes the signals of each array element to generate array output data; the array data is used to represent the signal strength distribution in the spatial direction, which facilitates interference identification and signal enhancement.

[0032] In another embodiment, it is assumed that the array in the system contains 64 array elements, the signal amplitude of each array element is between 0 and 1V, and the initial phase error is within ±3°; the signal processing unit normalizes the amplitude, compensates for the phase, and then performs weighted superposition to output 64 channels of array data, each channel of data containing 2048 sampling points, which are used for subsequent covariance matrix calculation.

[0033] Step S3: Calculate the covariance information of the array data and identify the interference subspace; determine the interference direction of the interference subspace and obtain the interference signal; use the array signal to suppress the interference signal and determine it as the anti-interference signal.

[0034] In one embodiment, the system calculates the covariance matrix using array data and uses eigenvalue decomposition to separate the signal subspace and interference subspace; the interference direction is determined by the eigenvector direction corresponding to the largest eigenvalue; the interference direction is suppressed using MVDR or minimum variance beamforming algorithm, thereby generating an anti-interference array output signal.

[0035] In another embodiment, assuming the covariance matrix has a dimension of 64×64, the top 3 eigenvalues ​​correspond to the directions of the interference signals with azimuth angles of 30°, 60°, and 90°, and elevation angles of 10°, 15°, and 5°, respectively. The system uses minimum variance beamforming to suppress the gain of the corresponding interference directions to -25dB, thereby obtaining an anti-interference signal output with a signal power of -65dBm to -55dBm.

[0036] Of particular importance is that step S3, which utilizes the array signal to suppress interference signals and generate anti-interference signals, includes:

[0037] The projection of each array element signal into the interference subspace is determined using the interference signal, thus obtaining the interference signal components;

[0038] In one embodiment, the system first calculates the projection of each element in the array onto the previously calculated interference subspace using the baseband signal of each element. The projection value represents the energy component of the element signal corresponding to the interference direction, and is used to quantify the contribution of the interference to each element signal.

[0039] In another embodiment, it is assumed that the array contains 32 elements, and the interference subspace consists of 5 interference directions. The energy of the first element projected into the interference subspace is 0.015V. 2 The projected energy of the second array element is 0.018V. 2 Similarly, the system records the projection result of each array element in the interference subspace for subsequent suppression operations.

[0040] Remove the interference signal components from the array signal and save the suppression results of each array element in the array element order;

[0041] In one embodiment, the system interference signal component is subtracted from the original baseband signal of each array element to obtain the interference-suppressed array signal. The suppression results are saved to the signal buffer in array element order to ensure the integrity of subsequent beam processing and time series analysis.

[0042] In another embodiment, assuming the original signal amplitude of the first array element is 1.05V, the corresponding interference projection energy is 0.015V. 2 After removing the interference components, the amplitude is 1.035V. The system repeats this operation on 32 array elements to generate a complete interference suppression array signal sequence.

[0043] The suppression results are normalized to generate an anti-interference signal.

[0044] In one embodiment, the system performs amplitude normalization processing on the interference-suppressed array signal, adjusting the amplitude of each array element signal to a uniform standard range to eliminate the impact of amplitude differences on subsequent beamforming and signal processing. The normalized array signal is the anti-interference signal, which can be directly used for satellite direction tracking or subsequent signal demodulation.

[0045] In another embodiment, assuming the normalized standard amplitude is 1V, the signal amplitude of the first array element after interference suppression is 1.035V, and the normalized amplitude is adjusted to 1V; the amplitude of the second array element after suppression is 1.012V, and the normalized amplitude is also 1V. The system performs the same operation on all array elements, generating 32 normalized anti-interference signal sequences to provide input for the next step of beamforming.

[0046] Step S4: Beamforming is performed on the anti-interference signal to determine the satellite direction, the carrier phase in that direction is tracked, and the pseudo-random code phase of the anti-interference signal is determined.

[0047] In one embodiment, the system performs beamforming on the target satellite direction based on the anti-interference signal, and achieves main lobe pointing towards the satellite direction through phase weighting and gain adjustment to suppress sidelobe interference; then it tracks the carrier phase in this direction and uses a phase-locked loop (PLL) to accurately lock the carrier; and determines the pseudo-random code phase through correlation decoding to achieve high-precision anti-interference signal positioning.

[0048] In another embodiment, assuming the target satellite is located at an azimuth angle of 45° and an elevation angle of 20°, with an anti-interference signal power of -60dBm, the system points the main lobe of the array towards the satellite and suppresses the side lobes to below -30dB. During tracking, the PLL locking error is less than 0.1rad, and the pseudo-random code phase determination accuracy is ±0.5 chips, ensuring the accuracy of subsequent navigation calculations.

[0049] Of particular importance, the beamforming process for counteracting interference signals in step S4 includes:

[0050] Extract the angle of arrival information of the anti-interference signal, including azimuth and elevation angles;

[0051] In one embodiment, the system extracts the angle of arrival (Angle of Arrival), including azimuth and elevation angles, from the anti-interference signal after interference suppression processing. The system combines the array's geometric position with time and frequency domain analysis of each array element signal, recording the element index and sampling time to provide basic data for subsequent path difference calculation.

[0052] In another embodiment, it is assumed that the anti-jamming signal comes from 3 satellites, and the array contains 32 array elements. The arrival angle information extracted by the system is as follows: satellite 1 azimuth 45°, elevation 30°; satellite 2 azimuth 120°, elevation 25°; satellite 3 azimuth 200°, elevation 40°. Each piece of information corresponds to the array element number (1~32) and the sampling time, and is recorded once every 10ms.

[0053] The propagation path difference is determined based on the angle of arrival information, thereby obtaining the phase delay value;

[0054] In one embodiment, the system calculates the propagation path difference of each array element based on its spatial position relative to a reference point and the angle of arrival information, thereby obtaining the phase delay value. Simultaneously, differences in array element gain and amplitude imbalances are considered to ensure the accuracy of the calculation.

[0055] In another embodiment, it is assumed that the propagation path difference and phase delay values ​​for some array elements are: 0.25 wavelengths / 90° for element 5, 0.125 wavelengths / 45° for element 12, 0.375 wavelengths / 135° for element 20, and 0.2 wavelengths / 72° for element 28. These values ​​are used for subsequent amplitude-weighted calculations.

[0056] The amplitude weighting value is calculated based on the phase delay value, and then applied to the anti-interference signal.

[0057] In one embodiment, the system calculates an amplitude weighting value based on the phase delay and amplitude information of each array element and applies it to the anti-jamming signal. The weighted array element signals are superimposed along the time sequence to form an energy-enhanced anti-jamming beam in the target direction. At the same time, the index, weighting coefficient, and sampling time of each array element are recorded to support subsequent satellite carrier phase tracking and pseudo-random code phase locking.

[0058] In another embodiment, the amplitude weighting values ​​are calculated as follows: 0.95 for element 5, 0.98 for element 12, 0.92 for element 20, and 0.97 for element 28. The weighted signals are superimposed sequentially according to the array elements to form an anti-interference beam. Simultaneously, the index, weighting coefficient, and sampling time of each array element are recorded for subsequent signal demodulation and positioning processing.

[0059] Preferably, step S1, which involves adding a synchronization timestamp to the radio frequency signal and performing frequency conversion processing to generate the baseband signal, includes:

[0060] Send a synchronization clock signal to the signal acquisition unit of the multi-element antenna array;

[0061] In one embodiment, the system sends a synchronization clock signal to the acquisition unit of the multi-element antenna array via a high-precision clock source (such as a GPS clock or an atomic clock) to ensure that each element samples under the same time reference. The clock signal can be transmitted to the ADC module of each element via optical fiber or coaxial cable to achieve nanosecond-level synchronization accuracy, thereby eliminating sampling time deviations between elements and ensuring the accuracy of subsequent phased array processing and interference suppression. The system can periodically monitor the clock locking status of each element and automatically adjust it when offset or drift is detected.

[0062] In another embodiment, assuming the array contains 32 elements, the system sends a synchronization clock frequency of 100MHz, and the clock signal received by each element is delayed within ±3ns; the clock signal is simultaneously transmitted to each element through an optical fiber distribution network to ensure strict alignment of the sampling times of the 32 RF signals. The system checks the phase-locked state of each element once per second and automatically relocks the clock when any node deviates by more than 5ns.

[0063] It receives radio frequency signals collected by a multi-element antenna array at the same time and adds a unified synchronization timestamp to each radio frequency signal;

[0064] In one embodiment, after the signal acquisition unit acquires the radio frequency signals of each array element, it sends the signals to the signal processing module. At the receiving end, the system adds a uniform synchronization timestamp to each radio frequency signal to achieve time alignment. The timestamp accuracy can reach the nanosecond level, ensuring the accuracy of phase information in subsequent filtering and frequency conversion processing. When receiving signals, the system can simultaneously record signal amplitude, frequency, and noise indicators, providing a reference for subsequent filtering and interference suppression.

[0065] In another embodiment, assuming the array has 64 elements, each element samples a radio frequency signal with a power range of -100dBm to -80dBm, and the sampling length is 2048 points; the system adds a synchronization timestamp with an accuracy of ±5ns to each signal to achieve time alignment of the 64 signals. At this time, each signal forms an independent buffer in memory, with its amplitude normalized to 0–1V for subsequent filtering and frequency conversion processing.

[0066] Calculate the filtering coefficients of the RF signal after the synchronization timestamp, and input them into the bandpass filter to generate the filtered signal;

[0067] In one embodiment, the system performs spectral analysis on each synchronized RF signal to determine the signal center frequency and bandwidth. Based on this, it calculates the filter coefficients of a bandpass filter, including the filter order, cutoff frequency, and gain parameters. Subsequently, the filter coefficients are applied to the RF signal to generate a bandpass filtered signal, effectively suppressing noise and interference frequency bands and ensuring signal quality. The system can dynamically adjust the filter parameters to adapt to changes in the signal environment.

[0068] In another embodiment, assuming the RF signal center frequency is 1.575 GHz, the filtering bandwidth is 2 MHz, and the filter order is 8, each signal, after being input to the filter, has an amplitude range of 0–1 V. After filtering, the sidelobe suppression reaches -30 dB, and the signal-to-noise ratio is improved by 10 dB. At this point, all 64 filtered signals are ready for the next frequency conversion processing stage.

[0069] The filtered signal is frequency-converted to determine the baseband signal.

[0070] In one embodiment, the system down-converts the bandpass-filtered radio frequency signal, mixes it using a local oscillator, and reduces the center frequency to zero to obtain the baseband signal. Simultaneously, it extracts the I / Q components to generate a complex baseband signal for subsequent array covariance matrix calculation, interference subspace identification, and phased array beamforming. The system also records the amplitude, phase, and signal power after frequency conversion for performance monitoring and subsequent signal correction.

[0071] In another embodiment, assuming the filtered signal frequency is 1.575 GHz, the center frequency of the down-converted baseband signal is 0 Hz, and the sampling rate is 50 MHz; each signal contains 2048 sampling points, the I / Q component amplitude range is -1V to 1V, and the baseband signal power is between -65 dBm and -55 dBm. The system buffers 64 baseband signals and prepares them for input to the covariance matrix calculation module to achieve interference identification and anti-interference signal generation.

[0072] Preferably, the filtered signal undergoes frequency conversion processing to determine the baseband signal, including:

[0073] Before frequency conversion, the filtered signal is input to the mixing unit, and the signal to be converted is marked in the mixing channel;

[0074] In one embodiment, the system inputs the bandpass-filtered radio frequency signal into the mixing unit, where each signal is marked as the signal to be converted in the channel. The mixing unit provides a reference signal through a local oscillator to achieve signal frequency shifting while maintaining the integrity of signal amplitude and phase information. Before mixing, the system performs amplitude normalization and status marking on the input signal to facilitate tracking and processing in subsequent stages.

[0075] In another embodiment, it is assumed that the array contains 32 filtered signals, each with an amplitude range of 0–1V and a power range of -65dBm to -55dBm; the mixing unit generates a unique identifier for each signal and assigns it to the mixing channel number 1–32; the system provides a reference signal with a frequency of 1.575GHz through a local oscillator to achieve initial signal shifting.

[0076] During the frequency conversion process, the first stage involves processing the high-frequency components of the signal to be converted, shifting the signal to be converted to the intermediate frequency range, and outputting an intermediate frequency signal segment.

[0077] In one embodiment, the system performs high-frequency component processing on the signal to be converted in the first stage, shifting the radio frequency signal from the original frequency band to the intermediate frequency (IF) range through mixing and filtering. The IF signal segment output in this stage retains complete amplitude and phase information for subsequent baseband conversion. Programmable mixer gain adjustment can be used during the processing to accommodate different signal strengths.

[0078] In another embodiment, assuming the original filtered signal frequency is 1.575 GHz, the system shifts it to the intermediate frequency range of 100 MHz–120 MHz; the amplitude range of each intermediate frequency signal is 0.2–0.8 V, and the number of sampling points is 2048; the system suppresses high-frequency noise through a digital filter, achieving a sidelobe suppression of -30 dB, and outputs an intermediate frequency signal segment to the second-stage processing unit.

[0079] During the frequency conversion process, the second stage converts the intermediate frequency signal segment into a baseband signal while correcting the phase shift.

[0080] In one embodiment, the system converts intermediate frequency signal segments into baseband signals in the second stage through mixing or digital-analog mixing; simultaneously, it performs phase correction on each signal to eliminate phase shifts caused by mixing, transmission delay, or device characteristics. After correction, the baseband signal retains its original amplitude, phase, and time series information intact, and can be used for array covariance matrix calculation, interference identification, and phased array beamforming.

[0081] In another embodiment, assuming the intermediate frequency signal segment has a frequency range of 100MHz–120MHz, a baseband signal with a center frequency of 0Hz is obtained after frequency conversion. The system performs ±0.1rad phase correction on each signal. The baseband amplitude range of the 64 signals is normalized to -1V to 1V, and each signal contains 2048 sampling points, ready to be input to the baseband signal buffer.

[0082] When outputting baseband signals, set the signal sampling parameters and push the generated baseband signals to the baseband signal buffer in batches according to the sampling order.

[0083] In one embodiment, the system sets the sampling rate, number of sampling points, and batch length for the baseband signal, and writes the baseband signal into a baseband signal buffer in batches according to time sequence so that the subsequent array processing module can read it sequentially. The buffer design ensures signal order and integrity, while supporting parallel writing and reading of multiple signals.

[0084] In another embodiment, it is assumed that the baseband signal sampling rate is 50MHz, and each batch of signals contains 512 sampling points; 64 signals are written to the buffer in batches according to the sampling order, and the push delay of each signal does not exceed 5μs; the buffer capacity is 4096 sampling points per channel, which supports buffering of 8 consecutive batches of signals, providing stable input for subsequent interference subspace analysis and beamforming.

[0085] Preferably, in step S2, inputting the baseband signal to the signal processing unit and performing phased array processing on each element of the baseband signal includes:

[0086] The baseband signal is input to the signal processing unit and divided into a high signal-to-noise ratio region, a medium signal-to-noise ratio baseband region, and a low signal-to-noise ratio baseband region.

[0087] In one embodiment, the system inputs the generated baseband signal into a signal processing unit to evaluate the signal-to-noise ratio (SNR) of each signal. Based on signal amplitude, noise power, and historical interference characteristics, the signal is divided into a high SNR region, a medium SNR baseband region, and a low SNR baseband region. During the division process, a sliding window method or statistical analysis method can be used to label the signals in different regions with separate processing strategies for subsequent weight calculation and weighted processing.

[0088] In another embodiment, assuming the input baseband signal consists of 64 channels, each containing 2048 sampling points; the signal-to-noise ratio (SNR) calculation results show that the high SNR region > 25 dB, accounting for 40% of the total signal points; the medium SNR region has an SNR between 15 and 25 dB, accounting for 35%; and the low SNR region has an SNR < 15 dB, accounting for 25%. The system stores the signal index of each region in a signal processing table to provide a basis for subsequent weighted instruction allocation.

[0089] In the high signal-to-noise ratio (SNR) baseband region, a fixed weight instruction is used; in the medium SNR baseband region, a minimum variance instruction is used; and in the low SNR baseband region, a balanced weighted instruction is used.

[0090] In one embodiment, the system directly applies preset fixed weights to the signal for high signal-to-noise ratio regions. This strategy simplifies calculations, improves processing speed, and fully utilizes the high-quality information of the signal itself to ensure array output stability and anti-interference performance.

[0091] In another embodiment, it is assumed that the high signal-to-noise ratio region contains a total of 819 sampling points, and the fixed weight of each array element is set to 1. All signals are weighted according to the same weight to calculate the array output. After processing, the signal amplitude is between 0.8 and 1.0V, and no further dynamic adjustment is required.

[0092] Preferably, in the high signal-to-noise ratio baseband region, the fixed weight instruction includes:

[0093] In the high signal-to-noise ratio baseband region, each array element channel in the array is assigned a pre-set amplitude weight; the baseband signals acquired by each array element are amplitude-weighted according to the amplitude weight; the weighted high signal-to-noise ratio baseband signals are superimposed along the time series to form the array output vector;

[0094] In one embodiment, the system assigns a pre-defined amplitude weight to each array element channel in the high signal-to-noise ratio (SNR) baseband region. The baseband signal acquired by each array element is amplitude-weighted according to the corresponding amplitude weight to ensure that the high SNR signal contributes to the array output to the maximum extent. The weighted signals are then superimposed point by point along the time series to form the array output vector, providing the basic signal for beamforming.

[0095] In another embodiment, assuming the array contains 32 elements and there are 819 sampling points in the high signal-to-noise ratio region, the system assigns an amplitude weight to each element channel, ranging from 0.85 to 1.0; the weighted signal amplitude ranges from 0.7 to 1.0V. The system superimposes the 32 weighted signals point by point along the time series to generate an array output vector with an amplitude range of approximately 0.8 to 2.5V, providing gain for the high signal-to-noise ratio signal.

[0096] Repeat the above operation at each sampling point in the high signal-to-noise ratio baseband region to generate a high signal-to-noise ratio baseband beam, while attaching the element index and timestamp.

[0097] In one embodiment, the system repeats the amplitude weighting and superposition operation described above for each sampling point in the high signal-to-noise ratio (SNR) baseband region to generate a complete high SNR baseband beam. Each output beam is appended with an element index and a sampling timestamp to facilitate subsequent array processing, interference suppression, and beam tracking.

[0098] In another embodiment, it is assumed that there are 819 sampling points in the high signal-to-noise ratio region, and each sampling point forms a 32-channel weighted superimposed signal to generate an array output vector. The system adds an element index (1–32) and a timestamp (sampling interval 20ns) to each output vector, and finally generates a complete high signal-to-noise ratio baseband beam sequence, providing accurate input for subsequent beamforming, target tracking and interference suppression.

[0099] Preferably, in the mid-signal-to-noise ratio baseband region, the minimum variance instruction includes:

[0100] In the medium signal-to-noise ratio (SNR) baseband region, the SNR baseband signal is divided into several frames of data according to the sampling points; the array covariance of each frame of data is calculated, and the minimum variance weight is calculated based on the covariance;

[0101] In one embodiment, the system divides the signal in the baseband region with medium signal-to-noise ratio into several frames of data according to sampling points, with each frame containing a fixed number of sampling points. The array covariance matrix is ​​calculated for each frame of data, and the minimum variance weight vector for each array element is solved according to the minimum variance criterion. This is used to minimize the output power while maintaining the desired signal directional gain, thereby achieving interference suppression and signal enhancement.

[0102] In another embodiment, assuming there are 716 sampling points in the medium signal-to-noise ratio region, these are divided into 64 sampling points per frame, forming 11 frames in total; the array contains 32 array elements. The system calculates the covariance matrix for each frame and obtains the minimum variance weight vector, with the weight of each array element ranging from 0.55 to 0.85; applying this weight can suppress interference signals by approximately -12 dB while maintaining the desired signal directional gain.

[0103] The minimum variance weights are applied to the medium signal-to-noise ratio (MSNR) baseband signals of each array element and then superimposed sequentially to form an MSNR baseband beam. The beam frame is then pushed to the signal processing buffer.

[0104] In one embodiment, the system applies the minimum variance weight of each frame to the mid-signal-to-noise ratio (MSNR) baseband signal of each array element, and sequentially superimposes them in a time sequence to form an MSNR baseband beam. The generated beam frames are pushed sequentially to the signal processing buffer, providing real-time input for subsequent array processing, interference analysis, or beamforming.

[0105] In another embodiment, assuming the amplitude of the 32-channel weighted signal in the first frame is 0.5–0.8V, it is superimposed in time sequence to form an array output vector; after repeating the operation for all 11 frames, a complete medium signal-to-noise ratio baseband beam sequence is generated. The system pushes each frame beam to the signal processing buffer, with a push delay of less than 5μs per frame. The buffer can continuously store approximately 2 seconds of signal data, ensuring stable and continuous subsequent processing.

[0106] Preferably, in the low signal-to-noise ratio baseband region, the equalization weighting instruction includes:

[0107] In the low signal-to-noise ratio (SNR) baseband region, the phase shift of the low SNR signal in each array element channel is calculated to obtain the array element amplitude and phase response; the equalization weight is determined based on the array element amplitude and phase response.

[0108] In one embodiment, the system calculates the phase offset of each array element channel signal in the low signal-to-noise ratio baseband region to obtain the array element amplitude and phase response. Initial equalization weights are determined based on the amplitude and phase response and used for subsequent signal amplitude and phase consistency correction and weighting processing.

[0109] In another embodiment, it is assumed that the array contains 32 array elements, and there are 1024 sampling points in the low signal-to-noise ratio region. The system calculates the phase offset range of -20° to +15° and the amplitude response range of 0.3–0.6V for each array element signal; based on this, initial equalization weights are generated, with amplitude weights ranging from 0.8 to 1.0 and phase correction values ​​ranging from -15° to +10°.

[0110] In the frequency domain, each frame of low signal-to-noise ratio baseband signal is divided into several sub-bands, the energy of each sub-band is counted, the weighting coefficients of each sub-band are adjusted, and an updated equalization weight is formed.

[0111] In one embodiment, the system divides each frame of low signal-to-noise ratio (SNR) baseband signal into several sub-bands in the frequency domain, calculates the energy of each sub-band, and adjusts the weighting coefficients of each sub-band according to the energy distribution to generate updated equalization weights. This step can improve the amplitude and phase consistency of signals in different frequency bands and enhance the array output quality in the low SNR region.

[0112] In another embodiment, assuming each frame contains 64 sampling points, it is divided into 8 sub-bands. The energy range of each sub-band is 0.02–0.15V. 2 The system calculates weighting coefficients based on subband energy, with an amplitude adjustment range of 0.85–1.05. The updated equalization weights are supplemented with phase correction for the next weighting process.

[0113] The updated equalization weights are applied to the low signal-to-noise ratio baseband signal of each array element, and amplitude-phase consistency correction is performed on each sampling point to generate the equalized low signal-to-noise ratio baseband signal.

[0114] In one embodiment, the system applies the updated equalization weights to each low signal-to-noise ratio (SNR) baseband signal in the array, performs amplitude and phase consistency correction on each sampling point, and generates an equalized low SNR baseband signal. This operation can reduce the impact of phase distortion and amplitude imbalance on the array beam.

[0115] In another embodiment, it is assumed that the amplitude weighted range of the first array element signal is 0.4–0.6V, and the phase offset is controlled within ±5° after phase correction; after repeating the operation on 32 array elements, a low signal-to-noise ratio baseband signal after equalization is obtained.

[0116] The equalized low signal-to-noise ratio (SNR) baseband signals are sequentially superimposed according to the time sequence to form a low SNR baseband beam, and the beam frame is pushed to the signal processing buffer.

[0117] In one embodiment, the system sequentially superimposes the equalized low signal-to-noise ratio (SNR) baseband signals in a time sequence to form a low SNR baseband beam, and pushes the generated beam frame to the signal processing buffer to provide input for subsequent array processing or interference suppression.

[0118] In another embodiment, it is assumed that there are 1024 sampling points in the low signal-to-noise ratio region, with 64 sampling points per frame. The equalization signals of 32 array elements are superimposed sequentially to form the array output vector. The system pushes the output beam of each frame to the signal processing buffer, which can store 2 seconds of signal data to ensure beam continuity and real-time processing.

[0119] Preferably, in step S3, calculating the covariance information of the array data and identifying the interference subspace includes:

[0120] Calculate the mutual deviation between any two array element signal sequences in the array data;

[0121] Based on the mutual deviation, the direction of the signal combination with the smallest deviation in the array data is determined. The signal energy corresponding to this direction is regarded as the higher signal direction and is determined as the signal subspace. The rest are interference subspaces.

[0122] In one embodiment, the system timestamps the radio frequency signals acquired by the multi-element antenna array, generates a filtered signal through a bandpass filter, and then converts the filtered signal into a baseband signal through a mixer and two-stage frequency conversion processing. Simultaneously, phase offset is corrected, and the signal is pushed to the baseband signal buffer in the sampling order. Subsequently, the system divides the baseband signal into high signal-to-noise ratio (SNR), medium SNR, and low SNR baseband regions. In the high SNR region, a preset amplitude weight is assigned to each element channel in the array, the signal is amplitude-weighted, and the weights are superimposed along the time sequence to generate a high SNR baseband beam, while also adding element indices and timestamps. In the medium SNR region, the signal is divided into several frames of data according to sampling points, the array covariance of each frame is calculated, a minimum variance weight is generated, and the weights are applied to each element signal and then superimposed sequentially to form a medium SNR baseband beam, which is then pushed to the signal processing buffer. In the low signal-to-noise ratio (SNR) region, the system calculates the amplitude and phase responses of each array element channel, determines the equalization weights, divides the signal into several sub-bands in the frequency domain, calculates the sub-band energy adjustment weighting coefficients, applies the updated equalization weights to each array element signal, performs amplitude and phase consistency correction on the sampling points, and then superimposes them to generate a low SNR baseband beam, which is then pushed to the signal processing buffer. Simultaneously, the system calculates the mutual deviation between any two array element signals in the array data, identifies the array element combination direction with the smallest deviation, determines its signal energy as the signal subspace, and classifies the other directions as interference subspaces. This subspace information is then used for subsequent minimum variance weighting or beamforming processing.

[0123] In another embodiment, it is assumed that the array contains 32 array elements, with 819 sampling points in the high SNR region, 1024 sampling points in the medium SNR region, and 512 sampling points in the low SNR region. In the high SNR region, the amplitude weight of each array element is preset to 1.0–1.2; in the medium SNR region, the minimum variance weight is calculated to be 0.6–0.85 after covariance calculation; and in the low SNR region, the updated sub-band equalization weight ranges from 0.5–0.9. In the mutual deviation calculation, the deviation of the combination of array elements 5, 12, and 19 is 0.008. This is the minimum value, corresponding to a signal energy of 2.8. This is determined to be a signal subspace; the energy range of the remaining 29 array elements combined signal is 0.2–0.9. The signal subspace is identified as an interference subspace. The system writes the signal subspace and interference subspace information into the array subspace buffer, setting the refresh interval to 5μs, for subsequent beamforming and interference suppression processing, thus achieving continuous operation of desired signal enhancement and interference suppression.

[0124] Preferably, the mutual deviation between any two array element signal sequences in the array data includes:

[0125] Extract the signal sequences of any two array elements from the array data, and denote them as the first array element signal sequence and the second array element signal sequence, respectively.

[0126] In one embodiment, the system first selects any two array elements from the baseband signal acquired by the multi-element antenna array. For each array element, its continuous sampling points within a specified time window are extracted to generate a complete signal sequence. The first array element signal sequence and the second array element signal sequence are used for subsequent amplitude and phase consistency analysis, respectively. During the extraction process, the sampling timestamp and array element index are recorded simultaneously to ensure the traceability of timing and array element information.

[0127] In another embodiment, it is assumed that the array contains 32 array elements, and each signal sequence contains 819 sampling points. The system selects array elements 5 and 12 as the analysis objects and extracts their baseband signal sequences within a continuous 5ms time window. The extracted signal sequences are stored in the array signal buffer module to provide raw data for subsequent deviation calculations.

[0128] Calculate the amplitude difference between the first array element signal sequence and the second array element signal sequence; calculate the phase deviation between the first array element signal sequence and the second array element signal sequence.

[0129] In one embodiment, the system performs amplitude and phase analysis on the first array element signal sequence and the second array element signal sequence, respectively. The amplitude difference is obtained by averaging the sum of squared amplitude differences at each sampling point, reflecting the consistency of the two signals in amplitude; the phase deviation is obtained by averaging the sum of squared phase differences at each sampling point, reflecting the consistency of the two signals in phase. During the calculation process, abnormal sampling points can be removed to reduce the impact of noise on the deviation.

[0130] In another embodiment, assuming the average amplitude of the signal sequence of the 5th element is 1.05V and the average amplitude of the signal sequence of the 12th element is 1.02V, the amplitude difference is calculated to be 0.007V. 2 Meanwhile, the calculated average phase difference is 0.004 rad. 2 The amplitude difference and phase deviation values ​​will be used as inputs for subsequent weighted fusion.

[0131] The mutual deviation is determined by weighting and fusing the amplitude deviation value and the phase deviation value.

[0132] In one embodiment, the system performs a weighted fusion of the amplitude difference and phase deviation values ​​calculated in step 2 according to preset weighting coefficients. Specifically, the formula can be: ;

[0133] In this context, the amplitude and phase of w are weighting coefficients, summing to 1. The generated mutual deviation index is used to evaluate the consistency of the two array element signals and serves as the basis for signal subspace identification and interference subspace partitioning.

[0134] In another embodiment, assuming the amplitude weight is set to 0.6 and the phase weight to 0.4, the mutual deviation between the 5th and 12th array elements is: 0.6 × 0.007 + 0.4 × 0.004 = 0.0058. The system repeats this calculation for all element combinations in the array, generating a 32 × 32 deviation matrix. The combination with the smallest deviation in this matrix is ​​marked as the signal subspace, and the remaining combinations are marked as the interference subspace, providing a decision-making basis for subsequent minimum variance beamforming and anti-interference processing.

[0135] Preferably, this specification also provides an adaptive anti-jamming signal processing system based on a GNSS multi-element phased array, used to execute the adaptive anti-jamming signal processing method based on a GNSS multi-element phased array as described above. This adaptive anti-jamming signal processing based on a GNSS multi-element phased array includes:

[0136] The frequency conversion processing module 101 is used to acquire the radio frequency signal of the multi-element antenna array, add a synchronization timestamp to the radio frequency signal, and perform frequency conversion processing to generate a baseband signal;

[0137] The phased array processing module 102 is used to input the baseband signal to the signal processing unit, perform phased array processing on each element of the baseband signal, and output array data.

[0138] The anti-interference signal generation module 103 is used to calculate the covariance information of the array data, identify the interference subspace, determine the interference direction of the interference subspace, obtain the interference signal, and use the array signal to suppress the interference signal of the array output, which is determined as the anti-interference signal.

[0139] The random code phase determination module 104 is used to perform beamforming on anti-interference signals, determine the satellite direction, track the carrier phase in that direction, and determine the pseudo-random code phase of the anti-interference signal.

[0140] Therefore, the embodiments should be considered as exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0141] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A GNSS multi-element phased array based adaptive anti-jamming signal processing method, characterized in that, The method is applied to a GNSS receiving system, the GNSS receiving system comprising a multi-element antenna array and a signal processing unit, and the method comprises the following steps: Step S1: acquiring radio frequency signals of the multi-element antenna array, adding a synchronous timestamp to the radio frequency signals, and performing frequency conversion processing to generate baseband signals; Step S2: inputting the baseband signals to the signal processing unit, performing phased array processing on each element of the baseband signals, and outputting array data, wherein the inputting of the baseband signals to the signal processing unit and the phased array processing on each element of the baseband signals in step S2 comprise: inputting the baseband signals to the signal processing unit and dividing the baseband signals into a high signal-to-noise ratio region, a medium signal-to-noise ratio baseband region, and a low signal-to-noise ratio baseband region; in the high signal-to-noise ratio baseband region, a fixed weight instruction is used; in the medium signal-to-noise ratio baseband region, a minimum variance instruction is used; and in the low signal-to-noise ratio baseband region, an equalization weighting instruction is used; Step S3: calculating covariance information of the array data, identifying an interference subspace, determining an interference direction of the interference subspace, obtaining an interference signal, and determining an anti-interference signal by using an array signal to suppress the array output of the interference signal; Step S4: performing beamforming on the anti-interference signal, determining a satellite direction, tracking a carrier phase in the direction, and determining a pseudo-random code phase of the anti-interference signal.

2. The GNSS-based multi-element phased array adaptive interference mitigation signal processing method of claim 1, wherein, The adding of the synchronous timestamp to the radio frequency signals and the frequency conversion processing to generate the baseband signals in step S1 comprise: sending a synchronous clock signal to a signal acquisition unit of the multi-element antenna array; receiving radio frequency signals collected by the multi-element antenna array at the same time, and adding a uniform synchronous timestamp to each radio frequency signal; calculating filter coefficients of the radio frequency signals after the synchronous timestamp, and inputting the filter coefficients to a band-pass filter to generate filter signals; performing frequency conversion processing on the filter signals to determine the baseband signals.

3. The GNSS-based multi-element phased array adaptive interference mitigation signal processing method of claim 2, wherein, The frequency conversion processing on the filter signals to determine the baseband signals comprises: before the frequency conversion processing, inputting the filter signals to a mixing unit and marking the to-be-converted signals in a mixing channel; in the frequency conversion process, in a first stage, performing high-frequency component processing on the to-be-converted signals, shifting the to-be-converted signals to an intermediate frequency range, and outputting an intermediate frequency signal segment; in the frequency conversion process, in a second stage, converting the intermediate frequency signal segment into a baseband signal while correcting a phase offset; when the baseband signals are output, setting signal sampling parameters, and pushing the generated baseband signals to a baseband signal buffer area in a sampling order. 4.The GNSS multi-element phased array based adaptive anti-jamming signal processing method according to claim 1, characterized in that, The use of the fixed weight instruction in the high signal-to-noise ratio baseband region comprises: in the high signal-to-noise ratio baseband region, pre-set amplitude weight values are given to each element channel in the array; the baseband signals collected by the elements are amplitude-weighted according to the amplitude weight values; and the weighted high signal-to-noise ratio baseband signals are superimposed along a time sequence to form an array output vector; the above operations are repeated at each sampling point in the high signal-to-noise ratio baseband region to generate a high signal-to-noise ratio baseband beam, and an element index and a timestamp are additionally attached.

5. The GNSS-based multi-element phased array adaptive interference mitigation signal processing method of claim 1, wherein, The use of the minimum variance instruction in the medium signal-to-noise ratio baseband region comprises: In the medium signal-to-noise ratio baseband region, the medium signal-to-noise ratio baseband signal is divided into several frame data according to sampling points; the array covariance of each frame data is calculated, and the minimum variance weight is calculated according to the covariance; the minimum variance weight is applied to the medium signal-to-noise ratio baseband signal of each element of the array, and is sequentially superimposed to form a medium signal-to-noise ratio baseband beam, and the beam frame is pushed to a signal processing buffer. 6.The GNSS multi-element phased array based adaptive interference mitigation signal processing method of claim 1, wherein, In the low signal-to-noise ratio baseband region, the equalization weighting instruction includes: In the low signal-to-noise ratio baseband region, the phase offset of the low signal-to-noise ratio signal of each array element channel in the low signal-to-noise ratio baseband signal is calculated to obtain the array element amplitude and phase response; the equalization weight is determined according to the array element amplitude and phase response; In the frequency domain, each frame of low signal-to-noise ratio baseband signal is divided into several subbands, the energy of each subband is counted, the weighting coefficient of each subband is adjusted, and the updated equalization weight is formed; The updated equalization weight is applied to the low signal-to-noise ratio baseband signal of each element of the array, and the amplitude and phase consistency of each sampling point is corrected to generate an equalized low signal-to-noise ratio baseband signal; The equalized low signal-to-noise ratio baseband signal is sequentially superimposed in time sequence to form a low signal-to-noise ratio baseband beam, and the beam frame is pushed to a signal processing buffer. 7.The GNSS multi-element phased array based adaptive interference mitigation signal processing method of claim 1, wherein, In step S3, the covariance information of the array data is calculated, and the interference subspace is identified, including: The mutual deviation degree of any two array element signal sequences in the array data is calculated; Based on the mutual deviation degree, the signal combination direction with the minimum deviation degree in the array data is determined, the signal energy corresponding to the direction is regarded as a higher signal direction, and the direction is determined as a signal subspace, and the rest is an interference subspace.

8. The GNSS-based multi-element phased array adaptive interference mitigation signal processing method of claim 7, wherein, The mutual deviation degree of any two array element signal sequences in the array data includes: Extracting the signal sequences of any two array elements of the array data, respectively denoted as a first array element signal sequence and a second array element signal sequence; The amplitude difference degree of the first array element signal sequence and the second array element signal sequence is calculated; the phase deviation value of the first array element signal sequence and the second array element signal sequence is calculated; The amplitude deviation value and the phase deviation value are weighted and fused to determine the mutual deviation degree.

9. A GNSS multi-element phased array based adaptive interference mitigation signal processing system, characterized in that, The GNSS multi-array phased array based adaptive anti-jamming signal processing method for executing the GNSS multi-array phased array based adaptive anti-jamming signal processing method according to claim 1 includes: A frequency conversion processing module is configured to acquire radio frequency signals of a multi-array antenna array, add a synchronous time stamp to the radio frequency signals, and perform frequency conversion processing to generate baseband signals; A phased array processing module is configured to input the baseband signals to a signal processing unit, perform phased array processing on each array element of the baseband signals, and output array data; An anti-jamming signal generation module is configured to calculate the covariance information of the array data, identify an interference subspace, determine an interference direction of the interference subspace, obtain an interference signal, and determine an anti-jamming signal by suppressing the interference signal in the array output of the array signal; A random code phase determination module is configured to perform beamforming on the anti-jamming signal, determine a satellite direction, track the carrier phase of the direction, and determine the pseudo-random code phase of the anti-jamming signal.

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