Satellite navigation anti-cheating method based on multi-means joint detection suppression

Abstract

The invention discloses a satellite navigation anti-cheating method based on multi-means joint detection suppression, and belongs to the technical field of satellite navigation and wireless communication. The method comprises the following steps: grading preprocessing: suppressing a high-intensity deception jamming signal to a medium-low intensity level through space-time adaptive processing, and enabling the high-intensity deception jamming signal and a real signal to enter a subsequent detection process together; detecting three dimensions of power, multiple correlation peaks of code phases and abnormal navigation messages for the preprocessed deception jamming signals; and performing feed-forward integrity verification and positioning calculation on the detected satellite signals by using pseudo-range consistency verification and receiver autonomous integrity monitoring verification. According to the method, the real-time performance and the processing efficiency of a receiver on navigation system application are guaranteed, the identification probability of low-intensity and complex forwarding mode deception jamming signals is improved, and the reliability, the availability and the continuity of navigation positioning results are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation and wireless communication technology, and specifically to a satellite navigation anti-spoofing method based on multi-method joint detection and suppression. Background Technology

[0002] With the widespread application of the BeiDou-3 Global Navigation Satellite System in key sectors such as national defense, transportation, and power, the security of its satellite navigation signals has become an indispensable core infrastructure supporting the national PNT (Positioning, Navigation, and Timing) system. However, satellite navigation signals are extremely weak (approximately -130 dBm) after transmission through space, making them vulnerable to malicious interference. Currently, jamming techniques are evolving towards diversification and lower cost, among which deceptive jamming has attracted significant attention due to its strong concealment and high hazard. This type of jamming generates false signals that are highly similar to real navigation signals, tricking receivers into outputting incorrect positioning, velocity, or time information, posing a serious threat to the timing terminals of high-value military platforms and critical infrastructure. Based on differences in signal processing depth, forwarding deception can be divided into three modes: direct forwarding (code phase delay < 1 chip), refined forwarding (delay 1.5-100 chips), and recording and playback forwarding (delay > 100 chips). Their different code phase and power characteristics pose multidimensional challenges to the receiver's detection and suppression capabilities.

[0003] Current anti-spoofing technologies have significant limitations: On the one hand, existing solutions lack the ability to adaptively grade and process interference intensity, failing to effectively suppress high-intensity spoofing at the front end, thus wasting baseband processing resources, and also struggling to detect low-intensity spoofing with power close to the real signal. On the other hand, most technologies rely solely on a single detection dimension such as power or code phase, lacking robustness in complex electromagnetic environments. Furthermore, they lack a unified identification framework for the three forwarding modes mentioned above, particularly exhibiting weak identification capabilities for large-delay signals in recording, playback, and forwarding. In addition, traditional receiver autonomous integrity monitoring (RAIM) is typically used as a post-event verification method, failing to form a feedforward closed loop with signal-level detection. After the spoofing interference signal is eliminated, positioning service often interrupts due to insufficient available satellites. These deficiencies severely restrict the reliable operation of navigation systems in adversarial environments. Summary of the Invention

[0004] To address the aforementioned issues, this invention aims to provide a satellite navigation anti-spoofing method based on multi-method joint detection and suppression. By constructing a three-layer collaborative processing architecture of "intensity-level preprocessing - multi-dimensional feature fusion detection - integrity feedforward verification", the real-time performance and processing efficiency of the receiver for navigation system applications are guaranteed, the probability of identifying low-intensity and complex forwarding pattern spoofing interference signals is improved, and the reliability, availability and continuity of navigation and positioning results are ensured.

[0005] The technical solution of this invention is: a satellite navigation anti-spoofing method based on multi-method joint detection and suppression, comprising the following steps:

[0006] Step 1, graded preprocessing: Through space-time adaptive processing, the high-intensity spoofing interference signal is suppressed to a medium-low intensity level, so that it enters the subsequent detection process together with the real signal;

[0007] Step 2, Multi-dimensional Feature Fusion Detection: The deception interference signal preprocessed in Step 1 is detected in three dimensions: power, code phase multi-correlation peaks, and navigation message anomalies.

[0008] Step 3, Autonomous Integrity Monitoring: Utilizing the redundant observations of the navigation system itself and the motion continuity of the platform carried by the receiver, the credibility of the satellite signals detected through multi-dimensional feature fusion is verified at the final level to ensure the reliability and usability of the positioning results after eliminating deceptive interference signals;

[0009] Step 4: Utilize all verified satellite observations to perform the final navigation and positioning calculation, and output reliable position, velocity, and time information.

[0010] Furthermore, the specific steps of step 1 are as follows:

[0011] Step 1.1, Signal Strength Assessment and Classification: Evaluate the interference-to-signal ratio (ISR) of the digital intermediate frequency (IF) signal output from the RF front-end; based on the ISR assessment results, classify the signal into three categories according to its strength: high-intensity spoofing interference signal, medium-intensity spoofing interference signal, and low-intensity spoofing interference signal.

[0012] Step 1.2, High-intensity deception interference signal suppression: The high-intensity deception interference signal with a power 40dB higher than the real signal is suppressed by forming a deep null in the direction of its arrival through a space-time adaptive processing algorithm, so that the power is reduced to a medium and low intensity level.

[0013] Step 1.3: Medium-intensity and low-intensity deception interference signals are passed directly: The identified medium-intensity and low-intensity deception interference signals are not suppressed to maintain the integrity of their signal characteristics; these two types of signals, together with the suppressed high-intensity deception interference signals, are directly sent to the subsequent step 2 for in-depth analysis and identification.

[0014] Further, step 2 includes: signal power detection: statistically analyzing the carrier-to-noise ratio of the signal obtained in step 1; when the carrier-to-noise ratio exceeds the dynamic threshold determined based on the Neyman-Pearson criterion, the signal is determined to be a deceptive interference signal and is excluded; correlation peak detection: for signals that pass the power detection, utilizing the physical characteristic that the repeater-type deceptive interference signal is necessarily lagging in code phase, multipath or deceptive interference signals are identified and eliminated during the signal acquisition stage; navigation message anomaly detection: verifying the rationality and consistency of the navigation message content, thereby identifying deceptive interference signals whose message parameters have been tampered with or are abnormal.

[0015] Furthermore, in the correlation peak detection, for the signal that has passed the power detection, correlation calculation is performed in the frequency-code phase two-dimensional search domain using a parallel acquisition architecture based on Fast Fourier Transform to calculate the cross-correlation function between the received signal and the local pseudo-random code; an acquisition threshold is set, and peak values ​​are detected on the cross-correlation function results; when multiple correlation peaks exceeding the acquisition threshold are detected, the peak value that appears first in the code phase is determined to correspond to the real signal, and the signals corresponding to the other peak values ​​that lag behind in the code phase are excluded; when the difference between the signal-to-noise ratio of the secondary peak and the signal-to-noise ratio of the main peak and the difference in code phase are both less than the threshold, a narrow correlator verification mechanism is triggered; this mechanism uses a narrower correlation interval for fine measurement to distinguish between highly similar real signals and deceptive interference signals.

[0016] Furthermore, step 3 includes: pseudorange consistency check: using the continuity of motion of the platform mounted on the receiver to detect abnormal jumps in pseudorange observations caused by deceptive interference signals; RAIM verification: based on the geometric configuration, using the redundant observations of the navigation system itself to perform statistical checks and make a final decision on suspicious signals.

[0017] Furthermore, in the RAIM verification, at least four satellites will be selected from those that have passed the detection in steps 1 and 2 and have not been identified as suspicious by the pseudorange consistency test to construct a high-confidence reference constellation. The satellite signals identified as suspicious will be sequentially introduced into the above reference constellation for joint positioning calculation.

[0018] For each suspicious signal introduced, the sum of squared pseudorange residuals (SSE) is calculated. If the SSE value exceeds the protection threshold determined based on the system integrity risk requirements, the introduced suspicious signal is determined to be a deception interference signal or a fault signal and is ultimately eliminated. When the number of satellites used for positioning is less than four after eliminating the deception interference signal, the availability assurance strategy is triggered.

[0019] Furthermore, the protection threshold T is dynamically determined based on the integrity risk probability and the satellite's geometric configuration:

[0020] ;

[0021] Where n is the total number of satellites participating in the positioning calculation. For the allocated integrity risk probability, Let be the (1-α) quantile of a chi-square distribution with (n-4) degrees of freedom.

[0022] Furthermore, the availability assurance strategy is to relax the protection threshold of RAIM verification by 20%, that is, to adjust T to 1.2T, in order to prioritize ensuring positioning continuity.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] (1) Adaptive processing of interference intensity: This invention optimizes the allocation of baseband processing resources by suppressing high-intensity deception interference signals at the front end and coordinating the detection of low-intensity deception interference signals at the back end, thereby ensuring the real-time performance and processing efficiency of the satellite navigation and positioning system.

[0025] (2) Comprehensiveness and robustness of detection: This invention forms a complementary detection chain by detecting power, code phase multi-correlation peaks and navigation message anomalies in three dimensions, which significantly improves the probability of identifying low-intensity and complex forwarding pattern deception interference signals, while reducing the risk of false alarms and missed alarms.

[0026] (3) Integrity assurance of feedforward closed loop: The present invention places RAIM verification before the positioning solution stage, forming an effective feedforward closed loop with the hierarchical detection of deception interference signals, ensuring the reliability, availability and continuity of the positioning results after eliminating deception interference signals.

[0027] (4) High versatility: The method can effectively counter various deception modes such as direct forwarding, purified forwarding and recording and playback forwarding, and is applicable to various military and civilian navigation receivers with high requirements for accuracy and reliability. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of the workflow of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] This invention proposes a satellite navigation anti-spoofing method based on multi-method joint detection and suppression. This embodiment, through rigorous mathematical derivation and numerical calculation, realizes a joint detection and suppression method for forward-relay spoofing interference, possessing strength grading, multi-domain collaboration, and integrity feedforward verification capabilities. A three-layer collaborative processing architecture of "strength grading preprocessing - multi-dimensional feature fusion detection - integrity feedforward verification" is constructed.

[0032] like Figure 1 As shown, this invention proposes a satellite navigation anti-spoofing method based on multi-method joint detection and suppression, including the following steps:

[0033] Step 1, Hierarchical Preprocessing: This step aims to suppress high-intensity deception interference signals to low-to-medium intensity levels through space-time adaptive processing, enabling them to enter the subsequent detection process along with the real signals. This optimizes the allocation of processing resources and ensures the real-time performance of the system.

[0034] Step 1.1, Signal Strength Assessment and Classification: Evaluate the interference-to-signal ratio (ISR) of the digital intermediate frequency (IF) signal output from the RF front-end. Based on the assessment results, the signal will be classified into three categories according to its strength: high-intensity spoofing interference signal (ISR > 40 dB), medium-intensity spoofing interference signal (10 dB < ISR ≤ 40 dB), and low-intensity spoofing interference signal (ISR ≤ 10 dB).

[0035] Step 1.2, High-intensity spoofing interference signal suppression: The high-intensity spoofing interference signal with a power 40dB higher than the real signal is suppressed by forming a deep null in its direction of arrival through the space-time adaptive processing (STAP) algorithm, so that its power is reduced to medium and low intensity levels before proceeding to the subsequent processing flow.

[0036] Step 1.3: Pass-through of Medium and Low Intensity Signals: For the identified medium-intensity and low-intensity spoofing interference signals, no suppression processing is performed in this step to maintain the integrity of their signal characteristics. These two types of signals, along with the suppressed high-intensity spoofing interference signal, will be directly sent to the subsequent Step 2 for in-depth analysis and identification.

[0037] Step 2, Multi-dimensional Feature Fusion Detection: Perform multi-dimensional, in-depth feature analysis on the signal preprocessed in Step 1. By detecting multiple correlation peaks in power and code phase, and navigation message anomalies, a complementary detection chain is formed, which significantly improves the probability of identifying low-to-medium intensity and complex forwarding pattern deception interference signals, while reducing the risk of false alarms and missed alarms.

[0038] The specific steps are as follows:

[0039] Step 2.1, Signal Power Detection: By monitoring abnormal signal carrier-to-noise ratio, identify and eliminate deceptive interference signals whose power is significantly higher than normal due to artificial amplification.

[0040] The carrier-to-noise ratio (C / N0) of the signal obtained in step 1 is calculated. When the C / N0 exceeds the threshold based on the Neyman-Pearson criterion (with a preset false alarm probability of 10), the signal is considered to be at a certain level. - When the dynamic threshold is determined by ³), the signal is determined to be a deceptive interference signal and is excluded.

[0041] The threshold can be adaptively corrected by ±3dB according to changes in the ambient noise floor to cope with different electromagnetic environments.

[0042] For signals that have undergone RF front-end processing and contain deception interference Modeling:

[0043]

[0044] Where s(t) is the real signal, A·s(t-τ) is the deception interference signal, and n(t) is the noise.

[0045] Step 2.2, Multi-correlation peak detection of code phase: For signals that pass power detection, the physical characteristic that the repeater-type spoofing interference signal is necessarily lagging in code phase is used to identify and eliminate the spoofing interference signal during the signal acquisition stage.

[0046] For signals that pass power detection, correlation operations are performed in the frequency-code-phase two-dimensional search domain using a parallel acquisition architecture based on Fast Fourier Transform (FFT) to calculate the cross-correlation function between the received signal and the local pseudo-random code.

[0047] A capture threshold is set (this threshold can be dynamically adjusted according to the terminal application scenario), and peak values ​​are detected in the cross-correlation function results. When multiple correlation peaks exceeding the capture threshold are detected, the peak with the earliest code phase is determined to correspond to the real signal, and the signals corresponding to the other peaks with lagging code phases are excluded. When the difference between the signal-to-noise ratio of the secondary peak and the signal-to-noise ratio of the primary peak (the earliest peak) is less than threshold 1 (usually 5 dB) and the code phase difference is less than threshold 2 (usually 1 chip), the narrow correlator verification mechanism is triggered. This mechanism uses a narrower correlation interval for fine measurement to distinguish between highly similar real signals and deceptive interference signals.

[0048] Step 2.3. Navigation Message Anomaly Detection (Tracking Phase): Verify the rationality and consistency of the navigation message content to identify deceptive interference signals such as tampered or abnormal message parameters.

[0049] For signals that have been acquired and entered tracking mode, their navigation messages are analyzed to obtain key parameters such as satellite ephemeris, satellite clock error correction, and ionospheric delay correction. The analyzed parameter values ​​are compared with preset empirical ranges. For example, the absolute value of a normal satellite clock error correction is usually much less than 1 millisecond (ms), and the satellite orbital radius is unlikely to experience sudden jumps of hundreds of meters (e.g., >100m). If any monitored parameter exceeds its reasonable empirical range, the satellite signal is determined to be a deception or interference signal and is eliminated before positioning calculation. If all monitored parameters are normal, the signal proceeds to the subsequent integrity verification step.

[0050] Steps 2.1, 2.2, and 2.3 are not strictly sequential, but rather a parallel or flexible pipelined processing relationship. The receiver can flexibly invoke or combine these detection methods according to the signal processing stage (such as the acquisition stage and the tracking stage) and data availability. For example, power detection and acquisition multi-peak detection can be performed in parallel during the initial acquisition phase, while message information detection should be performed after the signal has been stably tracked and the message has been demodulated. This design ensures the timeliness and comprehensiveness of the detection.

[0051] Step 3, Autonomous Integrity Monitoring: Utilizing the redundant observations of the navigation system itself and the motion continuity of the platform carried by the receiver, the credibility of the satellite signals detected through multi-dimensional feature fusion is verified at the final level to ensure the reliability and usability of the positioning results after eliminating deceptive interference signals.

[0052] The specific steps are as follows:

[0053] Step 3.1, Pseudorange Consistency Check: Utilizing the continuity of motion of the platform mounted on the receiver, abnormal jumps in pseudorange observations caused by deception interference are detected. The principle is that, based on the pseudorange observation ρ from the previous moment... t-1 Doppler frequency shift f dEstimate the pseudorange at the current moment:

[0054]

[0055] Where λ is the carrier wavelength and Δt is the time interval between continuous observations. The pseudorange ρ actually measured at the current moment... t With the predicted pseudorange ρ̂ t If the absolute value of the difference between the two values ​​is less than the preset tolerance (usually 3 meters), it is considered that the pseudorange observation value of the satellite has an abnormal jump and does not have motion continuity, and is marked as a suspicious signal.

[0056] Step 3.2, RAIM verification: Based on the geometric configuration, use the navigation system's own redundant observations to perform statistical testing and make a final decision on suspicious signals.

[0057] From the satellites (signals) detected in steps 1 and 2 that were not identified as suspicious in step 3.1, at least four satellites are selected to construct a high-confidence reference constellation. Satellite signals identified as suspicious are then sequentially introduced into the aforementioned reference constellation for joint positioning calculation.

[0058] For each solution that introduces a suspicious signal, the sum of squared pseudorange residuals (SSE) is calculated. If the SSE value exceeds the system integrity risk requirement (typically 10), the solution is considered invalid. -5 If the protection threshold T is determined by the value of the signal per hour, the introduced suspicious signal is determined to be a deceptive interference signal or a fault signal, and is ultimately eliminated.

[0059] The protection threshold T can be dynamically determined based on the integrity risk probability and the satellite geometry:

[0060]

[0061] Where n is the total number of satellites participating in the positioning calculation. For the allocated integrity risk probability, Let be the (1-α) quantile of a chi-square distribution with (n-4) degrees of freedom.

[0062] When fewer than four satellites are available for positioning after eliminating deceptive interference signals, the system can trigger an availability assurance strategy. For example, the protection threshold for RAIM verification can be relaxed by 20% (i.e., T is adjusted to 1.2T) to prioritize ensuring positioning continuity.

[0063] Step 4: Utilize all verified satellite observations to perform the final navigation and positioning calculation, and output reliable position, velocity, and time (PVT) information.

[0064] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0065] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A satellite navigation anti-spoofing method based on multi-means joint detection inhibition, characterized in that, Comprising the following steps: Step 1, hierarchical pretreatment: by space-time adaptive processing, the high-intensity spoofing jamming signal is suppressed to a medium-low intensity level, so as to enter the subsequent detection process together with the real signal; Step 2, multi-dimensional feature fusion detection: the spoofing jamming signal after step 1 pretreatment is detected in three dimensions of power, code phase correlation peak and navigation message anomaly; Step 3, autonomous integrity monitoring: using the redundant observation of the navigation system itself and the motion continuity of the platform carried by the receiver, the satellite signal detected by the multi-dimensional feature fusion is finally verified for credibility to ensure the reliability and availability of the positioning result after the spoofing jamming signal is removed; Step 4, using all the verified satellite observation, the final navigation positioning solution is carried out, and the reliable position, velocity and time information is output.

2. The multi-approach joint detection and deception rejection based satellite navigation method according to claim 1, wherein, The specific steps of step 1 are: Step 1.1, signal strength evaluation and classification: the digital intermediate frequency signal output by the radio frequency front end is evaluated for jamming signal ratio; according to the evaluation result, the signal is divided into three categories according to intensity: high-intensity spoofing jamming signal, medium-intensity spoofing jamming signal and low-intensity spoofing jamming signal; Step 1.2, high-intensity spoofing jamming signal suppression: the high-intensity spoofing jamming signal with power higher than that of the real signal by 40 dB is suppressed by space-time adaptive processing algorithm to form a deep null in the direction of arrival, so that the power is reduced to a medium or low intensity level; Step 1.3, medium-intensity spoofing jamming signal and low-intensity spoofing jamming signal straight through: for the identified medium-intensity spoofing jamming signal and low-intensity spoofing jamming signal, no suppression is performed to maintain the integrity of the signal characteristics; these two types of signals will be directly sent to the subsequent step 2 for in-depth analysis and identification together with the suppressed high-intensity spoofing jamming signal.

3. The multi-approach joint detection and deception rejection based satellite navigation method according to claim 1, wherein, Step 2 includes: Signal power detection: the carrier-to-noise ratio of the signal obtained in step 1 is counted, and when the carrier-to-noise ratio exceeds the dynamic threshold determined based on the Neyman-Pearson criterion, the signal is determined to be a spoofing jamming signal and is excluded; Correlation peak detection: for the signal detected by power detection, the physical characteristics of the retransmission spoofing jamming signal, which must lag in code phase, are used to identify and exclude the spoofing jamming signal in the signal acquisition stage; Navigation message anomaly detection: the reasonableness and consistency of the navigation message content are checked to identify spoofing jamming signals with tampered or abnormal message parameters.

4. The multi-approach joint detection and spoofing rejection based satellite navigation method according to claim 3, characterized in that, In the correlation peak detection, For the signal detected by power detection, a parallel acquisition architecture based on fast Fourier transform is used to calculate the cross-correlation function of the received signal and the local pseudo-random code in the frequency-code phase two-dimensional search domain; Set the acquisition threshold to detect the peak value of the cross-correlation function result; when multiple correlation peaks exceeding the acquisition threshold are detected, the peak value corresponding to the real signal is determined to be the first peak value in code phase, and the remaining peak values corresponding to the signals lagging in code phase are excluded; when the difference between the signal-to-noise ratio of the second peak and the signal-to-noise ratio of the main peak and the code phase difference are both less than the threshold, the narrow correlator review mechanism is triggered; this mechanism uses a narrower correlation interval for fine measurement to distinguish between real signals and spoofing jamming signals that are highly close.

5. The multi-approach joint detection and deception rejection based satellite navigation method according to claim 1, characterized in that, The step 3 comprises: Pseudo-range consistency check: using the continuity of the motion of the platform carrying the receiver, detecting the abnormal jump of the pseudo-range observation caused by the spoofing jamming signal; RAIM verification: based on the geometric configuration, using the redundant observations of the navigation system itself, statistically testing and finally judging the suspicious signals.

6. The multi-approach joint detection based spoofing resistant method of satellite navigation according to claim 5, characterized in that, In the RAIM verification, at least four satellites are selected from the satellite signals detected by the step 1 and the step 2 and not identified as suspicious by the pseudo-range consistency check to construct a high-confidence reference constellation, and the satellite signals identified as suspicious are introduced into the reference constellation in turn for positioning calculation together; For each calculation of introducing the suspicious signal, the pseudo-range residual sum of squares is calculated; if the SSE value exceeds the protection threshold determined based on the system integrity risk requirement, it is determined that the suspicious signal introduced this time is a spoofing jamming signal or a fault signal, and is finally excluded; when the spoofing jamming signal is excluded, if the number of satellites used for positioning is less than four, the availability guarantee strategy is triggered.

7. The multi-approach joint detection based spoofing resistant method of satellite navigation according to claim 6, characterized in that, The protection threshold T is dynamically determined by the integrity risk probability and the satellite geometric configuration: ； where n is the total number of satellites participating in the positioning solution, is the assigned integrity risk probability, is the (1 - a) quantile of a chi-square distribution with (n - 4) degrees of freedom.

8. The multi-approach joint detection based spoofing resistant method of satellite navigation according to claim 7, characterized in that, The guarantee strategy is to relax the protection threshold of the RAIM verification by 20%, that is, to adjust T to 1.2T, to preferentially ensure the continuity of positioning.

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