Satellite navigation system-based deception jamming identification method and system

Abstract

The invention belongs to the technical field of Beidou navigation, and particularly relates to a deception jamming identification method and system based on a satellite navigation system. Comprising the following steps: receiving a satellite navigation signal, resolving an initial carrier-to-noise ratio mean value, resolving an incident angle, calculating a direction vector, carrying out beam forming weighted synthesis, demodulating an array carrier-to-noise ratio, smoothing the array carrier-to-noise ratio, calculating a threshold value, calculating an increased amplitude, judging positioning information of the output satellite navigation signal or a pseudo-random noise code (PRN) number by deception jamming, and the like. According to the method, the signals are received through the uniform rectangular array, the incident angle of the real satellite signals is focused by using the beam forming technology, and the difference of carrier-to-noise ratio amplification is quantized in combination with the threshold value, so that the deception source is accurately distinguished, and meanwhile, the self-adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm is adopted, so that the robustness of the deception source is improved. By means of time window statistics and historical weight synthesis, the influence of a complex electromagnetic environment is effectively eliminated, and the misjudgment rate is remarkably reduced.

Description

Technical Field

[0001] The present invention belongs to the field of Beidou navigation technology, and in particular relates to a deception interference identification method based on a satellite navigation system and a system thereof. Background Art

[0002] Global satellite navigation systems (GNSS), such as GPS and BeiDou, play an irreplaceable role in key areas such as transportation, logistics, surveying and mapping, and military with their high-precision positioning and timing capabilities. However, with the popularization of technology, the threat of deception and interference they face is becoming increasingly severe. Deception and interference sources transmit false signals that are highly similar to real satellite signals to mislead the positioning results of the receiver, which may lead to serious consequences such as vehicle navigation errors and failure of military operations, seriously threatening the safety and reliability of the system; Traditional anti-spoofing technologies mostly rely on signal feature analysis or encryption authentication, but have significant limitations in actual scenarios. For example, when a spoofing interference source uses a single antenna to transmit multiple interference signals, the elevation and azimuth angles of these signals when they reach the receiver are exactly the same, making it difficult to distinguish them through conventional spatial filtering or signal parameter differences. The real satellite signals have significant differences in their incident angles (elevation and azimuth) due to their spatial distribution characteristics. In addition, existing methods are not adaptable to dynamic environments, and fixed threshold detection is prone to misjudgment due to environmental noise or signal fluctuations, especially in complex electromagnetic environments, where reliability is low. Summary of the invention

[0003] 1. Technical issues to be resolved The present invention aims to solve the problems existing in the existing deception interference identification method of the satellite navigation system, including the limitations of signal feature analysis and the defects of insufficient adaptability to dynamic environment. To this end, the present invention proposes a deception interference identification method based on the satellite navigation system and its system, which 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 carrier-to-noise ratio increase, so as to achieve accurate distinction of the deception source. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and uses time window statistics and historical weight synthesis to effectively eliminate the influence of complex electromagnetic environment and significantly reduce the misjudgment rate.

[0004] (II) Technical solution The present invention is implemented through the following technical solution. The present invention provides a deception 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: 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 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 the direction vector: Calculating the direction vector of the antenna array according to the incident angle, and using the direction vector as a weighting coefficient; weighting coefficient 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 angle and azimuth angle in step c respectively; 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; 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; 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; The specific steps of the automatic smoothing algorithm 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; 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.

[0005] Preferably, in step S4, the value of s is 0.55.

[0006] Preferably, 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.

[0007] Preferably, in step a, the antenna array further 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.

[0008] Preferably, 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.

[0009] The present invention also provides a deception interference identification system based on a satellite navigation system, comprising: 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 , and matches the incident angle with a pre-generated lookup table to quickly obtain the direction vector; 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.

[0010] Preferably, the signal receiving module is further 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.

[0011] (III) Beneficial effects 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 quantifies the difference in the carrier-to-noise ratio increase in combination with a threshold, thereby achieving accurate distinction of deception sources. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and uses time window statistics and historical weight synthesis to effectively eliminate the influence of complex electromagnetic environments and significantly reduce the misjudgment rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 The figure is a flow chart of the identification method of the present invention.

[0013] Figure 2 This is a framework diagram of the identification system described in the present invention.

[0014] Figure 3 It is a three-dimensional coordinate axis diagram of the uniform rectangular array described in the present invention. DETAILED DESCRIPTION

[0015] Figure 1 As shown, the present invention provides a deception interference identification method based on a satellite navigation system, wherein the satellite navigation system includes a satellite navigation baseband and an antenna array, and the method includes the following steps: a. Receiving satellite navigation signals: receiving satellite navigation signals through an antenna array; the antenna array is a uniform rectangular array ( Figure 3 ), comprising M rows and N columns of antenna units, and the spacings between adjacent antenna units in the horizontal and vertical directions are 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 the direction vector: Calculating the direction vector of the antenna array according to the incident angle, and using the direction vector as a weighting coefficient; weighting coefficient 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 angle and azimuth angle in step c respectively; 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; 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; 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; The specific steps of the automatic smoothing algorithm 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; 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 there is deception interference, and the pseudo-random noise code PRN number of the satellite navigation signal is output; Wherein, the value of s in step S4 is 0.55; Wherein, 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; Wherein, in said step a, the antenna array further 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; Wherein, 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.

[0016] like Figure 2 As shown, the present invention also provides a deception interference identification system based on a satellite navigation system, comprising: 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 , and matches the incident angle with a pre-generated lookup table to quickly obtain the direction vector; 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 there is deception interference, and the pseudo-random noise code PRN number of the satellite navigation signal is output; The signal receiving module is further 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.

[0017] Working principle: Signal reception and spatial resolution: Uniform rectangular array: It consists of M rows and N columns of antenna elements, with horizontal and vertical spacings of and ,The array layout improves the accuracy of beamforming by expanding the spatial sampling range; Directional vector solution: Based on the phase difference of the signal reaching different antenna elements ( ), the resultant direction vector; Beamforming focusing: generating direction vectors, i.e. weighting coefficients (including the phase compensation weights of each antenna unit), and the output signal is synthesized by conjugate transpose weighted synthesis , so that the main beam is aligned with the real satellite direction, and the side lobes suppress interference signals; Dynamic analysis and smoothing of carrier-to-noise ratio: Initial carrier-to-noise ratio average: the initial signal quality index obtained after baseband demodulation; Array carrier-to-noise ratio after beamforming: The array carrier-to-noise ratio after focusing is significantly improved (the gain in the direction of the real signal is maximized and the interference signal is suppressed); Adaptive smoothing algorithm: Time window statistics: Calculate the mean of the C array C / N ratio data within the 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 , thus avoiding outlier interference; Temporary carrier-to-noise ratio generation, i.e. , where L is the sensitivity adjustment coefficient, the value range is 1.5≤L≤3, and the sensitivity is adjusted dynamically; Historical weight synthesis, that is (s=0.55), the corresponding smoothed carrier-to-noise ratio is obtained , thereby balancing real-time fluctuations with historical trends and reducing the impact of short-term noise; Threshold determination and exception handling: Threshold design, that is , the threshold is logarithmically related to the array size (M×N). The larger the size, the higher the beamforming gain and the lower the required array carrier-to-noise ratio increase threshold; Decision logic: If the smoothed carrier-to-noise ratio increase (smoothed carrier-to-noise ratio - initial carrier-to-noise ratio mean) ≥ F, it is determined to be a real signal and the positioning information is output; If the increase is less than F, it is judged as deception interference and a pseudo-random noise code (PRN) alarm is output; Abnormal reset mechanism: If 5 times in a row> , clear the time window data and reinitialize the statistics to prevent long-term interference from causing algorithm failure.

[0018] The spatial resolution capability of the present invention has breakthroughs: Through uniform rectangular array and beamforming, the traditional spatial filtering "angle difference distinction" is upgraded to "spatial energy focusing". Even if the incident angle of the deception signal and the real signal is the same, the directional gain difference (the real signal gain is times) to achieve accurate distinction; The dynamic adaptability of the present invention is significantly improved: The adaptive smoothing algorithm combines real-time statistics with historical weights (s=0.55), which can suppress short-term pulse noise (such as lightning interference) and slowly changing interference (such as multipath effect) in complex electromagnetic environments, and the misjudgment rate is reduced by more than 50% compared with the fixed threshold method; The present invention optimizes computational efficiency: Pre-generate the direction vector lookup table to avoid real-time calculation of the phase difference matrix, reducing the amount of calculation by about 70%; The time window length C can be adjusted dynamically according to the environment (e.g., C=10 in urban environment, C=5 in open environment), balancing real-time performance and stability; The anti-interference collaborative design of the present invention: The pre-filtering algorithm works in conjunction with beamforming to further improve the ability to suppress strong interference signals. Experiments show that deception signals can still be effectively identified at -20dB interference-to-signal ratio (JSR); The present invention has robustness and scalability: The dynamic threshold formula is compatible with array designs of different sizes (such as 4×4 or 8×8), and the system can further improve the resolution by increasing the number of antenna elements; The abnormal reset mechanism prevents the algorithm from failing due to long-term environmental changes (such as seasonal ionospheric disturbances), ensuring long-term operational reliability; 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 quantifies the difference in the carrier-to-noise ratio increase in combination with a threshold, thereby achieving accurate distinction of the deception source. At the same time, it adopts an adaptive carrier-to-noise ratio smoothing and anomaly detection algorithm, and uses time window statistics and historical weight synthesis to effectively eliminate the influence of complex electromagnetic environments and significantly reduce the misjudgment rate. That is, through the triple innovation of spatial domain focusing, threshold design and adaptive smoothing algorithm, the core pain points of traditional deception interference identification methods in antenna multi-path interference and complex environments are solved. The technical solution has both theoretical rigor and engineering practicality, and can be widely used in high-precision GNSS scenarios such as vehicle navigation, UAV positioning, and military reconnaissance, providing important guarantees for the safety and reliability of satellite navigation systems.

[0019] Example (car navigation system): Parameter configuration: Antenna array: uniform rectangular array, M = 2 rows, N = 2 columns, horizontal spacing d1 = λ / 2, vertical spacing d2 = λ / 2; Time window length C: 5; Sensitivity adjustment coefficient l: 2.0; Historical weight coefficient s: 0.55 Implementation steps: Receiving satellite navigation signals: Satellite navigation signals are received using a 2×2 antenna array at -129dBm.

[0020] Calculate the initial carrier-to-noise ratio and incident angle: The initial carrier-to-noise ratio of the satellite navigation signal calculated by satellite navigation baseband demodulation is 43dBHz; the incident angle of the GPS satellite with a PRN of 10 is the elevation angle The azimuth is 35° is 120°; Calculate the direction vector based on the angle of incidence:

[0021] The received satellite navigation signal is multiplied by the conjugate transposed matrix of the direction vector to generate an array output signal after beamforming; The array output signal is demodulated and the array carrier-to-noise ratio of the satellite navigation signal is recalculated (taking 6 carrier-to-noise ratios as an example): [42 43 44 44 45 43 …] The sliding window of the mean is: [42.5 43.0 43.2 43.6 43.8] The standard deviation window values ​​are: [0.2 0.7 0.7 1.0 0.6] The median of the five means and standard deviations is 43.2 and 0.7, and the temporary carrier-to-noise ratio is calculated as ; The smoothed carrier-to-noise ratio is calculated as ; The threshold is calculated ; The increase was calculated to be 41.91-43=-1.09; When the increase amplitude is less than the threshold, it is determined that deception interference exists 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 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.

55.

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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