A spoofing interference recognition method and system based on a satellite navigation system

Abstract

The present invention belongs to the technical field of Beidou navigation, and particularly relates to a spoofing interference recognition method and system based on a satellite navigation system, including the following steps: receiving satellite navigation signals, calculating the initial carrier-to-noise ratio mean, calculating the incident angle, calculating the direction vector, beamforming weighted synthesis, demodulating the array carrier-to-noise ratio, smoothing the array carrier-to-noise ratio, threshold calculation, increased amplitude calculation, and spoofing interference determination to output the positioning information of the satellite navigation signal or the pseudo-random noise code PRN number, etc. The present invention receives signals through a uniform rectangular array, uses beamforming technology to focus on the incident angle of the real satellite signal, and combines the threshold to quantify the difference in the increase of the carrier-to-noise ratio, so as to achieve precise discrimination of the spoofing source. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and uses the method of time window statistics and historical weight synthesis to effectively eliminate the influence of the complex electromagnetic environment and significantly reduce the false judgment rate.

Description

Technical Field

[0001] The present invention belongs to the technical field of Beidou navigation, and particularly relates to a spoofing interference recognition method and system based on a satellite navigation system. Background Art

[0002] Global Navigation Satellite Systems (GNSS), such as GPS, Beidou, etc., play an irreplaceable role in key fields such as transportation, logistics, surveying and mapping, and military, relying on their high-precision positioning and timing capabilities. However, with the popularization of technology, the threat of spoofing interference it faces is becoming increasingly severe. Spoofing interference sources emit false signals highly similar to real satellite signals, misleading the positioning results of receivers, which may lead to serious consequences such as vehicle navigation errors and military operation failures, seriously threatening the security and reliability of the system.

[0003] Traditional anti-spoofing technologies mostly rely on signal feature analysis or encryption authentication, but there are significant limitations in actual scenarios. For example, when a spoofing interference source uses a single antenna to emit multiple interference signals, the elevation angle and azimuth angle of these signals when reaching the receiver are exactly the same, making it difficult to distinguish them through conventional spatial filtering or signal parameter differences. Moreover, due to the spatial distribution characteristics of real satellite signals, there are significant differences in their incident angles (elevation angle and azimuth angle). In addition, the existing methods have insufficient adaptability to dynamic environments, and fixed-threshold detection is prone to misjudgment due to environmental noise or signal fluctuations, especially with low reliability in complex electromagnetic environments. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] The present invention aims to solve the problems existing in the spoofing interference recognition method in the existing satellite navigation system, including the limitations of signal feature analysis and the insufficient adaptability to dynamic environments. For this purpose, the present invention proposes a spoofing interference recognition method and system based on a satellite navigation system, which receives signals through a uniform rectangular array, uses beamforming technology to focus on the incident angles of real satellite signals, and combines thresholds to quantify the differences in the carrier-to-noise ratio increase, thereby achieving precise discrimination of spoofing sources. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and effectively eliminates the influence of complex electromagnetic environments and significantly reduces the misjudgment rate by means of time window statistics and historical weight synthesis.

[0006] (II) Technical Solutions

[0007] The present invention is realized through the following technical solutions. The present invention provides a spoofing interference recognition method based on a satellite navigation system, where the satellite navigation system includes a satellite navigation baseband and an antenna array. The method includes the following steps:

[0008] a. Receiving satellite navigation signals: Receiving satellite navigation signals through an antenna array; the antenna array is a uniform rectangular array, including M rows and N columns of antenna elements, and the spacings between adjacent antenna elements in the horizontal and vertical directions are and respectively, where both M and N are integers, and are both real numbers;

[0009] b. Calculating the initial carrier-to-noise ratio mean value: Based on the satellite navigation signals, calculating the initial carrier-to-noise ratio mean value of the satellite navigation signals through satellite navigation baseband demodulation;

[0010] c. Calculating the incident angle: Based on the satellite navigation signals, calculating the incident angle of the satellite navigation signals through satellite navigation baseband demodulation, where the incident angle includes the elevation angle and the azimuth angle;

[0011] d. Calculating the direction vector: Calculating the direction vector of the antenna array according to the incident angle and using the direction vector as the weighting coefficient; the weighting coefficient is calculated by the formula:

[0012] ;

[0013] where T is the transpose symbol;

[0014] represents the phase difference of the received signal generated by the antenna element in the M-th row and N-th column relative to the reference point when the satellite navigation signal arrives at the antenna array at the incident angle , and the reference point is the antenna element in the first row and first column;

[0015] is calculated by the formula:

[0016] ; is the wavelength of the satellite navigation signal received in step a; j is a complex number, and e is the natural base; and are the elevation angle and azimuth angle in step c respectively;

[0017] e. Beamforming weighted synthesis: Multiplying the received satellite navigation signals by the conjugate transpose matrix of the weighting coefficient to generate the array output signal after beamforming; the array output signal is calculated by the formula: , where H is the conjugate transpose symbol, x(t) is the satellite navigation signal in step a, is the weighting coefficient in step d;

[0018] f. Demodulation array carrier-to-noise ratio: Demodulate the output signal of the array, and recalculate the array carrier-to-noise ratio of the satellite navigation signal;

[0019] g. Smoothed array carrier-to-noise ratio: The array carrier-to-noise ratio is smoothed using an automatic smoothing algorithm to obtain the smoothed carrier-to-noise ratio;

[0020] The specific steps of the automatic smoothing algorithm are as follows:

[0021] S1: Set the time window length C, and store the most recently generated C array carrier-to-noise ratio data; each time the carrier-to-noise ratio is updated, remove the oldest array carrier-to-noise ratio data within the time window and add the newly generated array carrier-to-noise ratio data;

[0022] S2: Calculate the mean value of the C array carrier-to-noise ratio data within the time window and the standard deviation , and take the median of the C mean values and the standard deviation within the time window respectively to obtain the median mean value and the median standard deviation ;

[0023] The formula for the mean value is:

[0024] ;

[0025] The formula for the standard deviation is:

[0026] ; where is the array carrier-to-noise ratio in step f;

[0027] S3: Calculate the temporary carrier-to-noise ratio according to the median mean value and the median standard deviation , where L is the sensitivity adjustment coefficient, and the value range is 1.5 ≤ L ≤ 3;

[0028] S4: Synthesize through the weighted formula to obtain the smoothed carrier-to-noise ratio , s is the historical weight coefficient and the value is 0.5~0.6, is the smoothed carrier-to-noise ratio calculated in the previous time;

[0029] S5: At the first calculation, is set to the array carrier-to-noise ratio in step f; in subsequent calculations, the smoothed carrier-to-noise ratio needs to be iteratively updated, and the rule is: use the current smoothed carrier-to-noise ratio as the new , and repeat S2 - S4 to iteratively update the smoothed carrier-to-noise ratio;

[0030] h. Threshold calculation: The calculation formula for the threshold F is as follows:

[0031] ;

[0032] i. Increase amplitude calculation: Subtract the initial carrier-to-noise ratio mean in step b from the smoothed carrier-to-noise ratio in step g to obtain the increase amplitude;

[0033] j. Spoofing interference determination: Determine whether the increase amplitude is ≥ the threshold F;

[0034] When the increase amplitude ≥ the threshold, it is determined that there is no spoofing interference, and the positioning information of the satellite navigation signal is output;

[0035] When the increase amplitude < the threshold, it is determined that there is spoofing interference, and the pseudo-random noise code PRN number of the satellite navigation signal is output.

[0036] Preferably, in step S4, the value of s is 0.55.

[0037] Preferably, in step S5, if the smoothed carrier-to-noise ratio after iterative update is continuously greater than for 5 consecutive times, then clear all data in the time window and re-initialize step S1.

[0038] Preferably, in step a, the antenna array also performs anti-interference weighting processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the satellite navigation signal after anti-interference processing.

[0039] Preferably, in step c and step d, the direction vector and its corresponding incident angle are stored in a pre-generated look-up table for quickly matching the weighting coefficient.

[0040] The present invention also provides a spoofing interference identification system based on a satellite navigation system, including:

[0041] A signal receiving module, configured as a uniform rectangular antenna array of M rows and N columns, with the adjacent antenna element spacings in the horizontal and vertical directions being and respectively, for receiving satellite navigation signals;

[0042] An initial carrier-to-noise ratio calculation module, connected to the signal receiving module, for calculating the initial carrier-to-noise ratio mean through satellite navigation baseband demodulation;

[0043] An incident angle calculation module, connected to the signal receiving module, configured to calculate the incident angle of the signal through satellite navigation baseband demodulation, where the incident angle is the elevation angle and the azimuth angle , and match the incident angle with a pre-generated look-up table to quickly obtain the direction vector;

[0044] A weighted coefficient calculation module, connected to the incident angle calculation module, configured to calculate the direction vector of the antenna array according to the incident angle , and its calculation formula is:

[0045] ;

[0046] where T is the transpose symbol;

[0047] represents the phase difference of the received signal generated by the antenna element in the Mth row and Nth column relative to the reference point when the satellite navigation signal arrives at the antenna array at the incident angle , and the reference point is the antenna element in the first row and first column;

[0048] The calculation formula of is:

[0049] ;

[0050] is the wavelength of the step satellite navigation signal; j is a complex number, and e is the natural base;

[0051] A beamforming module, connected to the signal receiving module and the weighted coefficient calculation module, configured to multiply the received satellite navigation signal by the conjugate transpose matrix of the weighted coefficient to generate an array output signal after beamforming , and its calculation formula is: , where x(t) is the satellite navigation signal and H is the conjugate transpose symbol;

[0052] An array carrier-to-noise ratio demodulation module, connected to the beamforming module, for demodulating the array output signal , and calculating the array carrier-to-noise ratio;

[0053] A carrier-to-noise ratio smoothing module, connected to the array carrier-to-noise ratio demodulation module, configured to process the array carrier-to-noise ratio using an automatic smoothing algorithm to obtain a smoothed carrier-to-noise ratio, including:

[0054] A time window management unit, configured to set the time window length C and store the C most recently generated array carrier-to-noise ratio data; each time the carrier-to-noise ratio is updated, the oldest array carrier-to-noise ratio data within the time window is removed, and the newly generated array carrier-to-noise ratio data is added;

[0055] A statistical calculation unit, configured to statistically calculate the mean value of the C array carrier-to-noise ratio data within the time window and the standard deviation , and take the median of the C mean values and the standard deviation within the time window respectively to obtain the median mean value and the median standard deviation ;

[0056] Mean value The calculation formula is:

[0057] ;

[0058] Standard deviation The calculation formula is:

[0059] ; where is the array carrier-to-noise ratio;

[0060] The temporary carrier-to-noise ratio generation unit is configured to calculate the temporary carrier-to-noise ratio according to the median mean value and the median standard deviation , where L is the sensitivity adjustment coefficient, and the value range is 1.5 ≤ L ≤ 3;

[0061] The smoothing synthesis unit is configured to synthesize and obtain the smoothed carrier-to-noise ratio through a weighting formula, s is the historical weight coefficient and the value is 0.5~0.6, is the smoothed carrier-to-noise ratio calculated in the previous time;

[0062] The iterative update unit is configured to, when calculating for the first time, set it as the array carrier-to-noise ratio ; in subsequent iterations, the smoothed carrier-to-noise ratio is updated by the previous smoothing result;

[0063] The anomaly detection unit is configured to, if the smoothed carrier-to-noise ratio after iterative update is continuously greater than for 5 times, then clear the time window data and re-initialize;

[0064] The threshold calculation module is connected to the signal receiving module and is configured to calculate the threshold according to the formula at ;

[0065] The increase amplitude calculation module is connected to the initial carrier-to-noise ratio calculation module and the carrier-to-noise ratio smoothing module, and is used to calculate the difference between the smoothed carrier-to-noise ratio and the mean value of the initial carrier-to-noise ratio;

[0066] The interference determination module is connected to the threshold calculation module and the increase amplitude calculation module, and is configured to determine whether the increase amplitude is ≥ the threshold F;

[0067] When the increase amplitude ≥ the threshold, it is determined that there is no spoofing interference, and the positioning information of the satellite navigation signal is output;

[0068] When the increase amplitude < the threshold, it is determined that there is spoofing interference, and the pseudo-random noise code PRN number of the satellite navigation signal is output.

[0069] Preferably, the signal receiving module is further integrated with a filtering sub-module, which performs anti-interference weighting processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the satellite navigation signal after anti-interference processing.

[0070] (III) Beneficial Effects

[0071] The present invention receives signals through a uniform rectangular array, uses beamforming technology to focus on the incident angle of real satellite signals, and combines thresholds to quantify the differences in the increase of carrier-to-noise ratio, thereby achieving precise discrimination of spoofing sources. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and by means of time window statistics and historical weight synthesis, effectively eliminates the influence of complex electromagnetic environments and significantly reduces the false judgment rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0073] Figure 1 It is a schematic flow chart of the identification method described in the present invention.

[0074] Figure 2 It is a framework diagram of the identification system described in the present invention.

[0075] Figure 3 It is a three-dimensional coordinate axis diagram of the uniform rectangular array described in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0076] Figure 1 As shown, the present invention provides a spoofing interference identification method based on a satellite navigation system. The satellite navigation system includes a satellite navigation baseband and an antenna array. The method includes the following steps:

[0077] a. Receiving satellite navigation signals: receiving satellite navigation signals through the antenna array; the antenna array is a uniform rectangular array ( Figure 3 as shown), including M rows and N columns of antenna elements. The spacing between adjacent antenna elements in the horizontal and vertical directions is respectively and , both M and N are integers, and are both real numbers;

[0078] b. Calculating the initial carrier-to-noise ratio mean value: based on the satellite navigation signal, calculating the initial carrier-to-noise ratio mean value of the satellite navigation signal through demodulation by the satellite navigation baseband;

[0079] c. Calculating the incident angle: based on the satellite navigation signal, calculating the incident angle of the satellite navigation signal through demodulation by the satellite navigation baseband. The incident angle includes the elevation angle and the azimuth angle;

[0080] d. Calculate the direction vector: Calculate the direction vector of the antenna array according to the incident angle, and use the direction vector as the weighting coefficient; the weighting coefficient The calculation formula is:

[0081] ;

[0082] where, T is the transpose symbol;

[0083] represents the phase difference of the received signal generated by the antenna element in the Mth row and Nth column relative to the reference point when the satellite navigation signal arrives at the antenna array at the incident angle , and the reference point is the antenna element in the first row and first column;

[0084] The calculation formula is:

[0085] ; is the wavelength of the satellite navigation signal received in step a; j is a complex number, and e is the natural base; and are the elevation angle and azimuth angle in step c respectively;

[0086] e. Beamforming weighted synthesis: Multiply the received satellite navigation signal by the conjugate transpose matrix of the weighting coefficient to generate the array output signal after beamforming; the array output signal The calculation formula is: , H is the conjugate transpose symbol, x(t) is the satellite navigation signal in step a, is the weighting coefficient in step d;

[0087] f. Demodulate the carrier-to-noise ratio of the array: Demodulate the array output signal and recalculate the carrier-to-noise ratio of the satellite navigation signal for the array;

[0088] g. Smooth the carrier-to-noise ratio of the array: The carrier-to-noise ratio of the array is smoothed to obtain the smoothed carrier-to-noise ratio by using an automatic smoothing algorithm;

[0089] The specific steps of the automatic smoothing algorithm are:

[0090] S1: Set the time window length C and store the C most recently generated carrier-to-noise ratio data of the array; each time the carrier-to-noise ratio is updated, remove the oldest carrier-to-noise ratio data within the time window and add the newly generated carrier-to-noise ratio data;

[0091] S2: Statistically calculate the mean value and the standard deviation of the C carrier-to-noise ratio data within the time window, and for the C mean values and the standard deviation within the time window Take the median respectively to obtain the median mean value and the median standard deviation ;

[0092] The mean value is calculated by the formula:

[0093] ;

[0094] The standard deviation is calculated by the formula:

[0095] ; where is the array carrier-to-noise ratio in step f;

[0096] S3: Calculate the temporary carrier-to-noise ratio according to the median mean value and the median standard deviation , where L is the sensitivity adjustment coefficient, and the value range is 1.5 ≤ L ≤ 3;

[0097] S4: Synthesize to obtain the smoothed carrier-to-noise ratio through the weighted formula, s is the historical weight coefficient and the value is 0.5~0.6, is the smoothed carrier-to-noise ratio calculated in the previous time;

[0098] S5: At the first calculation, is set to the array carrier-to-noise ratio in step f; in each subsequent calculation, the smoothed carrier-to-noise ratio needs to be iteratively updated, and the rule is: use the current smoothed carrier-to-noise ratio as the new , and repeat S2 - S4 to iteratively update the smoothed carrier-to-noise ratio;

[0099] h. Threshold calculation: The formula for calculating the threshold F is:

[0100] ;

[0101] i. Increase amplitude calculation: Subtract the initial carrier-to-noise ratio mean value in step b from the smoothed carrier-to-noise ratio in step g to obtain the increase amplitude;

[0102] j. Spoofing interference determination: Determine whether the increase amplitude is ≥ the threshold F;

[0103] When the increase amplitude ≥ the threshold, it is determined that there is no spoofing interference, and output the positioning information of the satellite navigation signal;

[0104] When the increase amplitude < the threshold, it is determined that there is spoofing interference, and output the pseudo-random noise code PRN number of the satellite navigation signal;

[0105] Among them, in step S4, the value of s is 0.55;

[0106] Among them, in step S5, if the smoothed carrier-to-noise ratio after iterative update is greater than for 5 consecutive times, then all data in the time window is cleared and step S1 is re-initialized;

[0107] Among them, in step a, the antenna array also performs anti-jamming weighting processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the satellite navigation signal after anti-jamming processing;

[0108] Among them, in step c and step d, the direction vector and its corresponding incident angle are stored in a pre-generated look-up table for quickly matching the weighting coefficient.

[0109] As Figure 2 shown, the present invention also provides a spoofing interference recognition system based on a satellite navigation system, including:

[0110] A signal receiving module, configured as a uniform rectangular antenna array with M rows and N columns, and the adjacent antenna element spacings in the horizontal and vertical directions are and respectively, for receiving satellite navigation signals;

[0111] An initial carrier-to-noise ratio calculation module, connected to the signal receiving module, for calculating the average value of the initial carrier-to-noise ratio through satellite navigation baseband demodulation;

[0112] An incident angle calculation module, connected to the signal receiving module, configured to calculate the incident angle of the signal through satellite navigation baseband demodulation, and the incident angle is the elevation angle and the azimuth angle , and matching the incident angle with a pre-generated look-up table to quickly obtain the direction vector;

[0113] A weighting coefficient calculation module, connected to the incident angle calculation module, configured to calculate the direction vector of the antenna array according to the incident angle , and its calculation formula is:

[0114] ;

[0115] Among them, T is the transpose symbol;

[0116] is expressed as the phase difference of the received signal generated by the antenna element in the Mth row and Nth column relative to the reference point when the satellite navigation signal arrives at the antenna array at the incident angle , and the reference point is the antenna element in the 1st row and 1st column;

[0117] The calculation formula is:

[0118] ;

[0119] is the wavelength of the step satellite navigation signal; j is a complex number, and e is the natural base;

[0120] The beamforming module, connected to the signal receiving module and the weighting coefficient calculation module, is configured to multiply the received satellite navigation signal by the conjugate transpose matrix of the weighting coefficient to generate an array output signal after beamforming , and its calculation formula is: , where x(t) is the satellite navigation signal and H is the conjugate transpose symbol;

[0121] The array carrier-to-noise ratio demodulation module, connected to the beamforming module, is used to demodulate the array output signal , and calculate the array carrier-to-noise ratio;

[0122] The carrier-to-noise ratio smoothing module, connected to the array carrier-to-noise ratio demodulation module, is configured to process the array carrier-to-noise ratio using an automatic smoothing algorithm to obtain a smoothed carrier-to-noise ratio, including:

[0123] The time window management unit is configured to set the time window length C and store the most recently generated C array carrier-to-noise ratio data; each time the carrier-to-noise ratio is updated, the oldest array carrier-to-noise ratio data within the time window is removed, and the newly generated array carrier-to-noise ratio data is added;

[0124] The statistical calculation unit is configured to statistically calculate the mean value of the C array carrier-to-noise ratio data within the time window and the standard deviation , and take the median of the C mean values and the standard deviation within the time window respectively to obtain the median mean value and the median standard deviation ;

[0125] The mean value The calculation formula is:

[0126] ;

[0127] The standard deviation The calculation formula is:

[0128] ; where is the array carrier-to-noise ratio;

[0129] The temporary carrier-to-noise ratio generation unit is configured to calculate the temporary carrier-to-noise ratio and the median standard deviation based on the median mean value , where L is the sensitivity adjustment coefficient, and the value range is 1.5 ≤ L ≤ 3;

[0130] The smoothing synthesis unit is configured to synthesize the smoothed carrier-to-noise ratio through a weighting formula , s is the historical weight coefficient and its value is 0.5 to 0.6, is the smoothed carrier-to-noise ratio calculated in the previous time;

[0131] The iterative update unit is configured to, when calculating for the first time, be set as the array carrier-to-noise ratio ; in subsequent iterations, the smoothed carrier-to-noise ratio is updated from the previous smoothing result;

[0132] The anomaly detection unit is configured to, if the smoothed carrier-to-noise ratio after iterative update is continuously greater than for 5 consecutive times, then clear the time window data and re-initialize;

[0133] The threshold calculation module is connected to the signal reception module and is configured to calculate the threshold according to the formula at ;

[0134] The increase amplitude calculation module is connected to the initial carrier-to-noise ratio calculation module and the carrier-to-noise ratio smoothing module, and is used to calculate the difference between the smoothed carrier-to-noise ratio and the average value of the initial carrier-to-noise ratio;

[0135] The interference determination module is connected to the threshold calculation module and the increase amplitude calculation module, and is configured to determine whether the increase amplitude is ≥ the threshold F;

[0136] When the increase amplitude ≥ the threshold, it is determined that there is no spoofing interference, and the positioning information of the satellite navigation signal is output;

[0137] When the increase amplitude < the threshold, it is determined that there is spoofing interference, and the pseudo-random noise code PRN number of the satellite navigation signal is output;

[0138] Among them, the signal reception module also integrates a filtering sub-module, which performs anti-interference weighting processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the satellite navigation signal after anti-interference processing.

[0139] Working principle:

[0140] Signal reception and spatial resolution:

[0141] Uniform rectangular array: It is composed of M rows and N columns of antenna elements, and the horizontal and vertical spacings are respectively and , and the array layout improves the accuracy of beamforming by expanding the spatial sampling range;

[0142] Direction vector calculation: Based on the phase difference of the signal arriving at different antenna elements ( ), synthesize the direction vector;

[0143] Beamforming focusing: Generate the direction vector, i.e., the weighting coefficients (including the phase compensation weights of each antenna element), and synthesize the output signal through conjugate transpose weighting , align the main beam with the true satellite direction, and suppress the interference signal with the side lobe;

[0144] Carrier-to-noise ratio dynamic analysis and smoothing:

[0145] Initial carrier-to-noise ratio mean: Obtain the initial quality index of the signal after baseband demodulation;

[0146] Carrier-to-noise ratio of the array after beamforming: The carrier-to-noise ratio of the focused array is significantly improved (the gain in the true signal direction is maximized, and the interference signal is suppressed);

[0147] Adaptive smoothing algorithm:

[0148] Time window statistics: Calculate the mean value of C carrier-to-noise ratio data of the array within the time window and the standard deviation , and for the C mean values within the time window and the standard deviation take the median respectively to obtain the median mean and the median standard deviation , so as to avoid the interference of outliers;

[0149] Generate the temporary carrier-to-noise ratio, that is , where L is the sensitivity adjustment coefficient, and the value range is 1.5 ≤ L ≤ 3, dynamically adjusting the sensitivity;

[0150] Synthesize the historical weights, that is (s = 0.55), and obtain the corresponding smoothed carrier-to-noise ratio , further balancing the real-time fluctuation and the historical trend, and reducing the influence of short-term noise;

[0151] Threshold determination and anomaly handling:

[0152] Threshold design, that is , the threshold is logarithmically related to the array scale (M×N). The larger the scale, the higher the beamforming gain, and the lower the required increase threshold of the array carrier-to-noise ratio;

[0153] Decision logic:

[0154] If the increase in the smoothed carrier-to-noise ratio (smoothed carrier-to-noise ratio - initial carrier-to-noise ratio mean) ≥ F, it is determined as a real signal, and the positioning information is output;

[0155] If the increase < F, it is determined as spoofing interference, and a pseudo-random noise code (PRN) alarm is output;

[0156] Abnormal reset mechanism: If it is greater than for 5 consecutive times, clear the time window data and re-initialize the statistics to prevent the algorithm from failing due to long-term interference.

[0157] Breakthrough in the spatial domain resolution ability of the present invention:

[0158] Through a uniform rectangular array and beamforming, the "angle difference discrimination" of traditional spatial domain filtering is upgraded to "spatial domain energy focusing". Even if the incident angles of the spoofing signal and the real signal are the same, accurate discrimination can be achieved through the difference in direction gain (the gain of the real signal is times);

[0159] Significant improvement in the dynamic adaptability of the present invention:

[0160] The adaptive smoothing algorithm combines real-time statistics and historical weights (s = 0.55), which can suppress short-term pulse noise (such as lightning interference) and slow-varying interference (such as multipath effect) in a complex electromagnetic environment, and the misjudgment rate is reduced by more than 50% compared with the fixed threshold method;

[0161] Optimization of the calculation efficiency of the present invention:

[0162] Pre-generate the direction vector lookup table to avoid real-time calculation of the phase difference matrix, reducing the amount of operations by about 70%;

[0163] The time window length C can be dynamically adjusted according to the environment (such as C = 10 in urban environment and C = 5 in open environment) to balance real-time performance and stability;

[0164] Anti-interference collaborative design of the present invention:

[0165] The pre-filtering algorithm and beamforming work together to further improve the ability to suppress strong interference signals. Experiments show that spoofing signals can still be effectively identified at a -20dB jam-to-signal ratio (JSR);

[0166] The present invention has robustness and scalability:

[0167] The dynamic threshold formula is compatible with array designs of different scales (such as 4×4 or 8×8), and the system can further improve the resolution ability by increasing the number of antenna elements;

[0168] The abnormal reset mechanism prevents the algorithm from failing due to long-term environmental changes (such as seasonal ionospheric disturbances), ensuring the long-term operation reliability;

[0169] The present invention receives signals through a uniform rectangular array, uses beamforming technology to focus on the incident angle of real satellite signals, and combines thresholds to quantify the differences in the increase of carrier-to-noise ratio, thereby achieving precise discrimination of spoofing sources. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and by means of time window statistics and historical weight synthesis, effectively eliminates the influence of complex electromagnetic environments and significantly reduces the false judgment rate. That is, through the triple innovations of spatial domain focusing, threshold design, and adaptive smoothing algorithm, it solves the core pain points of traditional spoofing interference identification methods in multi-path interference of antennas and complex environments. Its technical solution combines theoretical rigor and engineering practicability, and can be widely applied to high-precision GNSS scenarios such as vehicle navigation, UAV positioning, and military reconnaissance, providing an important guarantee for the security and reliability of satellite navigation systems.

[0170] Example (vehicle navigation system):

[0171] Parameter configuration:

[0172] Antenna array: Uniform rectangular array, M = 2 rows, N = 2 columns, horizontal spacing d1 = λ / 2, vertical spacing d2 = λ / 2;

[0173] Time window length C: 5;

[0174] Sensitivity adjustment coefficient l: 2.0;

[0175] Historical weight coefficient s: 0.55

[0176] Implementation steps:

[0177] Receive satellite navigation signals:

[0178] Use a 2×2 antenna array to receive satellite navigation signals of -129 dBm.

[0179] Calculate the initial carrier-to-noise ratio and incident angle:

[0180] Use satellite navigation baseband demodulation to calculate that the initial carrier-to-noise ratio of the satellite navigation signal is 43 dBHz; the incident angle of the GPS satellite with PRN of 10 is the elevation angle is 35°, and the azimuth angle is 120°;

[0181] Calculate the direction vector according to the incident angle:

[0182]

[0183] Multiply the received satellite navigation signal by the conjugate transpose matrix of this direction vector to generate the array output signal after beamforming;

[0184] Demodulate the array output signal and recalculate the array carrier-to-noise ratio of the satellite navigation signal (taking 6 carrier-to-noise ratios as an example): [42 43 44 44 45 43 …]

[0185] The sliding window of the mean is: [42.5 43.0 43.2 43.6 43.8]

[0187] The standard deviation window value is: [0.2 0.7 0.7 1.0 0.6]

[0189] Take the median of the 5 means and standard deviations as 43.2 and 0.7, and calculate the temporary carrier-to-noise ratio as ;

[0190] The smoothed carrier-to-noise ratio is calculated as ;

[0191] The threshold is calculated as ;

[0192] The increase amplitude is calculated as 41.91 - 43 = -1.09;

[0193] When the increase amplitude < the threshold, it is determined that there is spoofing interference, and the pseudo-random noise code PRN number 10 of the satellite navigation signal is output.

Claims

1. A deception jamming identification method based on a satellite navigation system, wherein the satellite navigation system includes a satellite navigation baseband and an antenna array, characterized in that: The following steps are involved: a. Receiving satellite navigation signals: receiving satellite navigation signals through an antenna array; the antenna array is a uniform rectangular array, comprising M rows and N columns of antenna units, and the spacing between adjacent antenna units in the horizontal and vertical directions is respectively and , M and N are both integers, and are all real numbers; b. Calculate the initial carrier-to-noise ratio mean value: Based on the satellite navigation signal, the initial carrier-to-noise ratio mean value of the satellite navigation signal is calculated by satellite navigation baseband demodulation; c. Calculate the incident angle: Based on the satellite navigation signal, the incident angle of the satellite navigation signal is calculated by satellite navigation baseband demodulation, and the incident angle includes an elevation angle and an azimuth angle; d. Calculating a direction vector: Calculating a direction vector of the antenna array according to the incident angle, and using the direction vector as a weighting coefficient; e. Beamforming weighted synthesis: multiply the received satellite navigation signal by the conjugate transposed matrix of the weighting coefficient to generate the array output signal after beamforming; f. Demodulation array carrier-to-noise ratio: demodulating the array output signal and recalculating the array carrier-to-noise ratio of the satellite navigation signal; g. Smoothed array carrier-to-noise ratio: The array carrier-to-noise ratio is obtained by an automatic smoothing algorithm; h. Threshold calculation: The calculation formula of the threshold F is: ； i. Increase calculation: Subtract the smoothed carrier-to-noise ratio in step g from the initial carrier-to-noise ratio mean in step b to obtain the increase; j. Deception interference determination: determine whether the increase is ≥ threshold F; When the increase amplitude is greater than or equal to the threshold, it is determined that there is no deception interference and the positioning information of the satellite navigation signal is output; When the increase amplitude is less than the threshold, it is determined that deception interference exists and the pseudo-random noise code PRN number of the satellite navigation signal is output.

2. The method for identifying deception interference based on a satellite navigation system according to claim 1, characterized in that: The weighting coefficient in step d The calculation formula is: ； Where T is the transposition symbol; Expressed as the satellite navigation signal at an incident angle When it reaches the antenna array, the phase difference of the received signal generated by the antenna element in the Mth row and the Nth column relative to the reference point, where the reference point is the antenna element in the 1st row and the 1st column; The calculation formula is: ； is the wavelength of the satellite navigation signal received in step a; j is a complex number, and e is a natural base; and are the elevation and azimuth angles in step c respectively.

3. The method for identifying deception interference based on a satellite navigation system according to claim 1, characterized in that: In step e, the array output signal The calculation formula is: , H is the conjugate transpose symbol, x(t) is the satellite navigation signal in step a, is the weighting coefficient in step d.

4. The method for identifying deception interference based on a satellite navigation system according to claim 1, characterized in that: The specific steps of the automatic smoothing algorithm in step g are: S1: Set the time window length C to store the C array carrier-to-noise ratio data generated recently; each time the carrier-to-noise ratio is updated, remove the oldest array carrier-to-noise ratio data in the time window and add the newly generated array carrier-to-noise ratio data; S2: The mean of the C array signal-to-noise ratio data within the statistical time window and standard deviation , and the C means in the time window and standard deviation Take the median respectively to get the median mean and median standard deviation ; Mean The calculation formula is: ； Standard Deviation The calculation formula is: ;in, is the array carrier-to-noise ratio in step f; S3: Based on the median mean and median standard deviation Calculate temporary carrier-to-noise ratio , where L is the sensitivity adjustment coefficient, and its value range is 1.5≤L≤3; S4: Smoothed carrier-to-noise ratio obtained by weighted formula synthesis , s is the historical weight coefficient and its value is 0.5~0.6, is the smoothed carrier-to-noise ratio calculated last time; S5: When calculating for the first time, Set to the array carrier-to-noise ratio in step f ; In each subsequent calculation, the smoothed carrier-to-noise ratio It needs to be updated iteratively, and the rule is: the current smoothed carrier-to-noise ratio As new , and repeat S2-S4 to iteratively update the smoothed carrier-to-noise ratio.

5. The method for identifying deception interference based on a satellite navigation system according to claim 4, characterized in that: In step S4, the value of s is 0.

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6. The method for identifying deception interference based on a satellite navigation system according to claim 4, characterized in that: In step S5, if the iteratively updated smoothed carrier-to-noise ratio is > , then clear all data in the time window and reinitialize step S1.

7. The method for identifying deception interference based on a satellite navigation system according to claim 1, characterized in that: In step a, the antenna array also performs anti-interference weighted processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the anti-interference processed satellite navigation signal.

8. The method for identifying deception interference based on a satellite navigation system according to claim 1, characterized in that: In step c and step d, the direction vector and its corresponding incident angle are stored in a pre-generated lookup table for fast matching of weighting coefficients.

9. A deception jamming identification system based on a satellite navigation system, characterized in that: Included are: The signal receiving module is configured as a uniform rectangular antenna array with M rows and N columns, and the spacing between adjacent antenna units in the horizontal and vertical directions is and , used to receive satellite navigation signals; The initial carrier-to-noise ratio calculation module is connected to the signal receiving module and calculates the initial carrier-to-noise ratio mean value through satellite navigation baseband demodulation; The incident angle calculation module is connected to the signal receiving module and is configured to calculate the incident angle of the signal through satellite navigation baseband demodulation. The incident angle is the elevation angle. and azimuth ; The weighted coefficient calculation module is connected to the incident angle calculation module and is configured to calculate the direction vector of the antenna array according to the incident angle. , and its calculation formula is: ； Where T is the transposition symbol; Expressed as the satellite navigation signal at an incident angle When it reaches the antenna array, the phase difference of the received signal generated by the antenna element in the Mth row and the Nth column relative to the reference point, where the reference point is the antenna element in the 1st row and the 1st column; The calculation formula is: ； is the wavelength of the satellite navigation signal; j is a complex number, and e is a natural base; The beamforming module is connected to the signal receiving module and the weighting coefficient calculation module and is configured to multiply the received satellite navigation signal by the conjugate transposed matrix of the weighting coefficient to generate the array output signal after beamforming. , and its calculation formula is: , x(t) is the satellite navigation signal, H is the conjugate transposed symbol; Array carrier-to-noise ratio demodulation module, connected to the beamforming module, is used to demodulate the array output signal , calculate the array carrier-to-noise ratio; The carrier-to-noise ratio smoothing module is connected to the array carrier-to-noise ratio demodulation module and is configured to process the array carrier-to-noise ratio using an automatic smoothing algorithm to obtain a smoothed carrier-to-noise ratio, including: A time window management unit is configured to set a time window length C, store the C array carrier-to-noise ratio data generated most recently; each time the carrier-to-noise ratio is updated, remove the oldest array carrier-to-noise ratio data in the time window, and add the newly generated array carrier-to-noise ratio data; The statistical calculation unit is configured to calculate the mean of the C array C / N data within the statistical time window. and standard deviation , and the C means in the time window and standard deviation Take the median respectively to get the median mean and median standard deviation ; Mean The calculation formula is: ； Standard Deviation The calculation formula is: ;in, is the array carrier-to-noise ratio; A temporary carrier-to-noise ratio generating unit is configured to generate a signal based on a median mean and median standard deviation Calculate temporary carrier-to-noise ratio , where L is the sensitivity adjustment coefficient, and its value range is 1.5≤L≤3; A smoothing synthesis unit configured to obtain a smoothed carrier-to-noise ratio by synthesizing through a weighted formula , s is the historical weight coefficient and its value is 0.5~0.6, is the smoothed carrier-to-noise ratio calculated last time; Iterative update unit, configured for the first calculation, Set to array carrier-to-noise ratio ; Smoothed carrier-to-noise ratio in subsequent iterations Updated by the previous smoothing result; The anomaly detection unit is configured to detect if the smoothed carrier-to-noise ratio after iterative update is > , then clear the time window data and reinitialize; The threshold calculation module is connected to the signal receiving module and is configured to calculate the threshold value according to the formula Calculate the threshold value; An amplitude calculation module is added, which is connected to the initial carrier-to-noise ratio solution module and the carrier-to-noise ratio smoothing module to calculate the difference between the smoothed carrier-to-noise ratio and the initial carrier-to-noise ratio mean value; An interference determination module, connected to the threshold calculation module and the increase amplitude calculation module, configured to determine whether the increase amplitude is ≥ the threshold F; When the increase amplitude is greater than or equal to the threshold, it is determined that there is no deception interference and the positioning information of the satellite navigation signal is output; When the increase amplitude is less than the threshold, it is determined that deception interference exists and the pseudo-random noise code PRN number of the satellite navigation signal is output.

10. The deception interference identification system based on satellite navigation system according to claim 9, characterized in that: The signal receiving module is also integrated with a filtering submodule, which performs anti-interference weighted processing on the satellite navigation signal through a filtering algorithm, so that the satellite navigation signal is equal to the anti-interference processed satellite navigation signal.

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