Satellite navigation signal deception detection method

Abstract

The invention discloses a satellite navigation signal deception detection method, which comprises the following steps of: acquiring a satellite signal, outputting lead, instant and lag correlation values corresponding to a same-direction signal and an orthogonal signal of the satellite signal on the basis of a multi-correlator of a carrier loop and a code tracking loop; the correlation values which are output by the same-direction channel and the orthogonal channel and change along with the time are used for calculation to obtain M1 measurement and M2 measurement which change along with the time; and obtaining measurement thresholds of the M1 measurement and the M2 measurement based on a preset false alarm rate, and determining whether cheating exists based on the measurement thresholds. According to the method, two measurement criteria are designed, so that the deception detection performance of the system is further improved; meanwhile, the complexity and the hardware cost of the algorithm are lower than those of a traditional detection method assisted by external information.

Description

Technical Field

[0001] The invention relates to satellite signal detection technology and a method for detecting satellite navigation signal deception. Background Art

[0002] The widespread use of satellite navigation technology has significantly improved efficiency and accuracy across industries worldwide. First, the global coverage of satellite navigation ensures precise location, speed, and time information, whether in urban or rural areas, or in remote ocean and mountainous areas. This provides unprecedented reliability for transportation, logistics management, and rescue operations. Second, the high-precision positioning capabilities of satellite navigation systems enable safer operation of autonomous vehicles and precise sowing and harvesting by agricultural machinery, significantly improving production efficiency and reducing resource waste. Furthermore, satellite navigation technology is particularly useful in emergency rescue and disaster prevention and mitigation. During natural disasters, it can quickly provide the precise location of affected areas, assisting rescue teams in efficiently deploying resources, saving lives, and minimizing losses. Furthermore, in the development of smart cities, the integration of satellite navigation with technologies such as the Internet of Things and 5G is driving innovation in areas such as intelligent transportation and environmental monitoring, providing technical support for efficient urban operations and sustainable development.

[0003] However, due to the environmental and technical characteristics of satellite signal transmission, they are susceptible to interference and spoofing. First, satellite signals travel extremely long distances, making them extremely weak during propagation. This makes them more susceptible to various environmental and human interference. Furthermore, the relatively open nature of satellite navigation system signals makes them susceptible to spoofing. Spoofing can result in erroneous location information. Such spoofing attacks can not only lead to personal navigation errors but also have serious consequences for critical sectors such as the military, finance, and aviation.

[0004] Current spoofing detection methods fall into several categories. The first is receiver-autonomous spoofing detection methods using a single antenna. These methods can be implemented directly within the tracking loop and detect spoofed signals by comparing them with the real signal. These methods include signal quality monitoring (SQMT) and its variant, Doppler anomaly monitoring. Another category generally relies on external information, such as integrated GNSS / INS navigation using an antenna array. These methods offer good anti-spoofing capabilities, but their drawbacks include relatively high hardware costs and algorithmic complexity, which in turn increase the cost of their application.

[0005] Previous SQMT methods used the output results of the in-phase branch to construct the corresponding deception detection metric, but did not fully consider the energy changes in the orthogonal branch when being deceived. However, the interaction between the deceptive signal and the true signal will cause the correlated energy to leak into the orthogonal channel. Summary of the Invention

[0006] The object of the present invention is to provide a satellite navigation signal deception detection method which has the advantages of lower cost and lower computational complexity while ensuring high performance of deception detection.

[0007] In order to achieve the above tasks, the present invention adopts the following technical solutions:

[0008] A method for detecting satellite navigation signal deception, comprising:

[0009] Acquire satellite signals, and use a multi-correlator based on a carrier loop and a code tracking loop to output the corresponding leading, immediate, and lagging correlation values of the co-directional and quadrature signals of the satellite signals;

[0010] The time-varying correlation values output by the co-directional channel and the orthogonal channel are used to calculate the time-varying M1 and M2 metrics. The metric thresholds of the M1 and M2 metrics are obtained based on the preset false alarm rate, and whether deception occurs is determined based on the metric thresholds.

[0011] Furthermore, the M1 metric and the M2 metric are specifically expressed as:

[0012] M1 metric:

[0013]

[0014] M2 metric:

[0015]

[0016] Among them, M1(t) and M2(t) represent the values of M1 and M2 at time t respectively, I E (t), I P (t) and I L (t) are the leading, immediate and lagging correlation values of the same phase channel respectively; Q E (t) and Q L (t) are the leading and lagging correlation values of the orthogonal channel respectively.

[0017] Furthermore, the metric thresholds of the M1 metric and the M2 metric are obtained based on the preset false alarm rate, including:

[0018] First, in a no-deception scenario where only the real satellite signal system noise exists, determine the mean μ1 and variance σ1 of the M1 metric, as well as μ2 and variance σ2 of the M2 metric;

[0019] Secondly, set the corresponding false alarm rate P for M1 and M2 metrics 1FA 、P 2FA ,According to the normal distribution characteristics of the two metrics in the no-deception scenario, the corresponding metric thresholds are obtained respectively.

[0020] Furthermore, the mean μ1 and variance σ1 of the M1 metric are as follows:

[0021]

[0022]

[0023] Where σ0 represents the correlation noise variance, d represents the length of a C / A code chip, represents the interval between the leading code and the lagging code relative to the prompt correlator; τ represents the code phase of the signal, R(·) represents the autocorrelation function of the C / A code, and R(τ) represents the value of the autocorrelation function at the code phase τ.

[0024] Furthermore, μ2 and variance σ2 of the M2 metric are as follows:

[0025] μ2=(0.5π) 1 / 2 σ0

[0026]

[0027] Where σ0 represents the variance of the correlated noise.

[0028] Furthermore, the corresponding false alarm rate P is set for the M1 and M2 metrics. 1FA 、P 2FA , expressed as:

[0029]

[0030] Where x represents the metric variable, specifically M1(t) or M2(t); μ1 and σ1 are the mean and variance of the M1 metric, and μ2 and σ2 are the mean and variance of the M2 metric; Th 1l Th 1u is the lower and upper thresholds of the M1 metric; Th 2l Th 2u are the lower and upper thresholds of the M2 metric.

[0031] Furthermore, the corresponding metric thresholds are calculated based on the normal distribution characteristics of the two metrics in the non-deception scenario, including:

[0032]

[0033] Where erfc(t) represents the complementary error function, erfc -1 (x) refers to the inverse function of erfc(x), e represents a natural constant and t is a function variable.

[0034] Furthermore, determining whether fraud exists based on a metric threshold includes:

[0035] Plot the changes of M1 metric and M2 metric over time respectively to check whether there are time periods in which M1 metric and M2 metric are less than the corresponding lower threshold or greater than the corresponding upper threshold. If both are within the respective upper and lower threshold ranges or only exceed the upper and lower threshold ranges within the preset time, it is judged that there is no fraud; otherwise, it is considered that there is fraud.

[0036] Furthermore, after acquiring the satellite signal, the satellite signal receiver divides the satellite signal into two channels: an in-phase signal and an orthogonal signal. The in-phase signal and the orthogonal signal are first mixed and multiplied with the carrier generated by the local carrier generator through a carrier loop. In the in-phase channel, the signal is multiplied with a sine carrier generated by the carrier generator based on a sine table, while in the orthogonal channel, the signal is multiplied with a cosine carrier generated by the carrier generator based on a cosine table, thereby performing carrier stripping on the in-phase channel and the orthogonal channel respectively.

[0037] Three correlators, namely, advance, immediate and lag, are set in the co-directional channel and the orthogonal channel respectively; in the co-directional channel of the code tracking loop, the three C / A codes, namely advance, immediate and lag, generated by the code generator are correlated with the co-directional signal after carrier stripping and passed through an integrator-scavenger to obtain the advance, immediate and lag correlation values; similarly, in the orthogonal channel, the orthogonal signal is correlated with the three C / A codes and integrated to obtain the advance, immediate and lag correlation values.

[0038] A terminal device includes a processor, a memory, and a computer program stored in the memory; when the processor executes the computer program, the satellite navigation signal deception detection method is implemented.

[0039] A computer-readable storage medium stores a computer program; when the computer program is executed by a processor, the satellite navigation signal deception detection method is implemented.

[0040] Compared with the prior art, the present invention has the following technical features:

[0041] Compared with the traditional I-channel SQMT scheme, the present invention has better system performance in deception detection. The traditional scheme only uses the correlator output value of the in-phase channel. The present invention takes into account that in the absence of multipath or deception, the tracking loop can ensure that all energy remains in the in-phase channel and the victim receiver stably tracks the true signal. Therefore, the orthogonal channel is only noise. In most cases, when deception exists, the relative carrier phase will continue to change randomly. This is because it is almost impossible to use a completely aligned carrier phase to implement a deception attack. As the relative carrier phase changes, the energy of the true and false composite signal will fluctuate. In this case, the tracking loop cannot stably track the true signal, and abnormal energy will exist in the Q channel. In addition, the correlation value of the additional lead correlator will often be distorted first during the deception process. The present invention designs two measurement criteria to further improve the system's deception detection performance. At the same time, the algorithm complexity and hardware cost are not high compared to traditional detection methods that use external information as an aid. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a schematic diagram of the satellite signal spoofing process;

[0043] Figure 2 Schematic diagram of the receiver's loop for capturing and tracking satellite signals;

[0044] Figure 3 The M1 metric variation curve constructed for this scheme over time;

[0045] Figure 4 The M2 metric variation curve constructed for this scheme over time;

[0046] Figure 5 This is the curve of the joint detection results of M1 metric and M2 metric changing over time. DETAILED DESCRIPTION

[0047] like Figure 1 As shown, the satellite signal spoofing process is divided into the following stages:

[0048] A Initial phase; the spoof signal is active but still "far away" from the true correlation peak. The receiver should lock onto the true signal.

[0049] B. Approach phase: The peak of the counterfeit signal approaches the true peak. The receiver still tracks the true signal, but the additional correlator is able to detect the presence of the second peak in the search space.

[0050] C. Overlap phase: The false signal and the real signal are consistent. In this phase, the two peaks overlap, and the spoofer (the signal power transmitted is higher than the actual signal power) forces the signal to rise.

[0051] D. Decline phase: The power of the spurious signal is high enough to force the receiver to remain locked on the spurious signal, which is delayed to introduce a pseudo-spacing error. The real peak is shifted away.

[0052] The structures of the real signal and the deceptive signal can be expressed as:

[0053]

[0054] Where, subscript x a (t) and x s (t) represents the real signal and the deceptive signal respectively; A a (t), A s (t) represents the amplitude of the real satellite signal and the deceptive satellite signal, d a (t), d s (t) represents the real and spoofed navigation messages, respectively, c a (t), c s (t) represents the real and deceptive spreading codes, τ a (t), τ s (t) represents the code phase offset of the real and deceptive spreading codes, respectively, and f w Indicates the carrier frequency of the satellite signal, Δf a (t), Δf s (t) represents the Doppler shift of the real and deceptive satellite signals, Φ a (t), Φ s (t) represent the real spoofed satellite signal carrier phase offset.

[0055] To use the present invention to detect deception, it is necessary to use a receiver to capture and track satellite signals; Figure 2 This is a structural diagram of satellite signal capture and tracking in the present invention. The technical solution of the present invention is as follows:

[0056] A method for detecting satellite navigation signal spoofing, which utilizes the outputs of multiple correlators of a carrier tracking loop and a code tracking loop for receiving satellite signals to perform spoofing detection, comprises:

[0057] After acquiring the satellite signal, the satellite signal receiver divides it into two channels: an in-line signal and a quadrature signal. The in-line and quadrature signals are first mixed and multiplied with the carrier generated by the local carrier generator through a carrier loop. In the in-line channel, the signals are multiplied with a sine carrier generated by the carrier generator based on a sine table, while in the quadrature channel, the signals are multiplied with a cosine carrier generated by the carrier generator based on a cosine table. This allows carrier stripping of the in-line and quadrature channels, respectively.

[0058] Three correlators, namely, advance, immediate, and lag, are set in the co-directional channel and the orthogonal channel respectively; in the co-directional channel of the code tracking loop, the three C / A codes, namely, advance, immediate, and lag, generated by the code generator are correlated with the co-directional signal after carrier stripping and passed through an integrator-scavenger to obtain advance, immediate, and lag correlation values; similarly, in the orthogonal channel, the orthogonal signal is correlated with the three C / A codes and integrated to obtain advance, immediate, and lag correlation values; finally, these time-varying correlation values output by the co-directional channel and the orthogonal channel are used to calculate the time-varying M1 metric and M2 metric; based on a preset false alarm rate, the measurement thresholds of the M1 metric and the M2 metric are obtained, and the presence of deception is determined based on the measurement thresholds.

[0059] 1.M1 metric and M2 metric.

[0060] The present invention constructs two SQMT metrics for deception detection:

[0061] M1 metric:

[0062]

[0063] M2 metric:

[0064]

[0065] Among them, M1(t) and M2(t) represent the values of M1 and M2 at time t, respectively. Both values change with time. E (t), I P (t) and I L (t) are the leading, immediate and lagging correlation values of the same phase channel respectively; Q E (t) and Q L (t) are the leading and lagging correlation values of the orthogonal channel respectively.

[0066] In this scheme, a total of 6 correlators are set in the co-phase channel and the orthogonal channel during the code tracking process, and three correlation values of the co-phase channel, namely, half a chip ahead, half a chip behind, and instantaneous, are obtained. E , I L , and I P At the same time, for the orthogonal channel, we also need to obtain the three correlation values of delayed half a chip, advanced half a chip and immediate Q E , Q L and Q P .

[0067] If a received GNSS satellite signal contains a spoofed signal, the primary difference between it and the legitimate GNSS satellite signal lies in the pseudo-code phase. Therefore, real-time spoofing detection can be performed by studying the changes in the signal correlation peak shape caused by the code phase difference between the legitimate and spoofed signals.

[0068] 2. Determine the hypothesis test and define:

[0069]

[0070] In the non-spoofing scenario (only real satellite signals and system noise exist), I E (t), I P (t), I L (t) all obey the normal distribution. Generally speaking, their ratio no longer obeys the normal distribution. According to the derivation of scholars C Sun et al. and and The conclusion that it approximately obeys the normal distribution (https: / / scholar.google.com / citations?user=Dg7vdvAAAAAJ&hl=en&oi=sra); then the mean μ1 and variance σ1 of the M1 metric can be obtained by Taylor expansion:

[0071]

[0072] Where σ0 represents the correlation noise variance, d represents the length of a C / A code chip, represents the interval between the leading code and the lagging code relative to the prompt correlator; τ represents the code phase of the signal, R(·) represents the autocorrelation function of the C / A code, and R(τ) represents the value of the autocorrelation function at the code phase τ.

[0073] The processing of the M2 metric can also obtain the mean μ2 and variance σ2 in the non-deception scenario:

[0074] μ2=(0.5π) 1 / 2 σ0(6)

[0075]

[0076] 3. Determination of measurement threshold.

[0077] Set the corresponding false alarm rate P for M1 and M2 metrics 1FA 、P 2FA ,According to the normal distribution characteristics of the two metrics in the no-deception scenario, the corresponding metric thresholds are obtained respectively.

[0078]

[0079] Where x represents a metric variable, specifically M1(t) or M2(t).

[0080] Simplifying the above formulas (8) and (9), and combining the mean and variance of the M1 metric and the M2 metric, we can get the corresponding metric thresholds, including the lower threshold Th of the M1 metric.1l and upper threshold Th 1u , and the lower threshold Th of the M2 metric 2l and upper threshold Th 2u :

[0081]

[0082] Where erfc(t) represents the complementary error function, erfc -1 (x) refers to the inverse function of erfc(x), e represents a natural constant, and t represents the function variable.

[0083] 4. Deception determination based on M1 and M2 metrics.

[0084] Plot the changes of M1 and M2 metrics over time respectively to check whether there are time periods when M1 and M2 metrics are less than the corresponding lower threshold or greater than the corresponding upper threshold. If they are both within the respective upper and lower threshold ranges or only exceed the upper and lower threshold ranges within the preset time (a short millisecond time), it is judged that there is no deception and the decision H0 is made.

[0085] Assuming that both metrics exceed the corresponding upper and lower thresholds at the same time, the decision H1 is made, that is, it is judged that deception exists:

[0086] S=(M1<Th 1l ∪M1>Th 1u ;H1)∩(M2<Th 2l ∪M2>Th 2u ;H1)(14)

[0087] The method of the present invention utilizes the characteristics of the code loop correlation peak of the GNSS receiver, and does not ignore the influence of the deceptive signal on the orthogonal branch. It reduces the corresponding equipment cost without affecting the internal calculation complexity of the receiver, and has broad application prospects.

[0088] Example:

[0089] The deception detection results of the static scene in the Texas Spoofing Test Battery (TEXBAT) of the University of Texas using the M1 metric and the M2 metric according to the present invention are shown in Fig. Figure 5 ; The scene is:

[0090] (1) 0-120 seconds: No deception, same as the real original data.

[0091] (2) 120-180 seconds: Spoofing signal injection. The spoofing signal is identical to the real signal, and the superposition of the two enhances the carrier-to-noise ratio (CNR).

[0092] (3) 180-315 seconds: The spoof code phase is manipulated to gradually deviate from the true signal code phase until the interval is 2μs.

[0093] The detection results are similar to the real scene and the detection effect is good.

[0094] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for detecting satellite navigation signal deception, characterized in that: include: Acquire satellite signals, and use a multi-correlator based on a carrier loop and a code tracking loop to output the corresponding leading, immediate, and lagging correlation values of the co-directional and quadrature signals of the satellite signals; The time-varying correlation values output by the co-directional channel and the orthogonal channel are used to calculate the time-varying M1 and M2 metrics. The metric thresholds of the M1 and M2 metrics are obtained based on the preset false alarm rate, and whether deception occurs is determined based on the metric thresholds.

2. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: The M1 metric and the M2 metric are specifically expressed as: M1 metric: M2 metric: Among them, M1(t) and M2(t) represent the values of M1 and M2 at time t respectively, I E (t), I P (t) and I L (t) are the leading, immediate and lagging correlation values of the same phase channel respectively; Q E (t) and Q L (t) are the leading and lagging correlation values of the orthogonal channel respectively.

3. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: The thresholds for the M1 and M2 metrics are obtained based on the preset false alarm rates, including: First, in a no-deception scenario where only the real satellite signal system noise exists, determine the mean μ1 and variance σ1 of the M1 metric, as well as μ2 and variance σ2 of the M2 metric; Secondly, set the corresponding false alarm rate P for M1 and M2 metrics 1FA 、P 2FA ,According to the normal distribution characteristics of the two metrics in the no-deception scenario, the corresponding metric thresholds are obtained respectively.

4. The satellite navigation signal spoofing detection method according to claim 1, wherein: The mean μ1 and variance σ1 of the M1 metric are as follows: Where σ0 represents the correlation noise variance, d represents the length of a C / A code chip, represents the interval between the leading code and the lagging code relative to the prompt correlator; τ represents the code phase of the signal, R(·) represents the autocorrelation function of the C / A code, and R(τ) represents the value of the autocorrelation function at the code phase τ.

5. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: The μ2 and variance σ2 of the M2 metric are as follows: μ2=(0.5π) 1 / 2 s0 Where σ0 represents the variance of the correlated noise.

6. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: Set the corresponding false alarm rate P for M1 and M2 metrics 1FA 、P 2FA , expressed as: Where x represents the metric variable, specifically M1(t) or M2(t); μ1 and σ1 are the mean and variance of the M1 metric, and μ2 and σ2 are the mean and variance of the M2 metric; Th 1l Th 1u is the lower and upper thresholds of the M1 metric; Th 2l Th 2u are the lower and upper thresholds of the M2 metric.

7. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: Based on the normal distribution characteristics of the two metrics in a non-deception scenario, the corresponding metric thresholds are calculated, including: Where erfc(t) represents the complementary error function, erfc -1 (x) refers to the inverse function of erfc(x), e represents a natural constant and t is a function variable.

8. The satellite navigation signal spoofing detection method according to claim 1, wherein: Determines fraud based on metric thresholds, including: Plot the changes of M1 metric and M2 metric over time respectively to check whether there are time periods in which M1 metric and M2 metric are less than the corresponding lower threshold or greater than the corresponding upper threshold. If both are within the respective upper and lower threshold ranges or only exceed the upper and lower threshold ranges within the preset time, it is judged that there is no fraud; otherwise, it is considered that there is fraud.

9. The satellite navigation signal spoofing detection method according to claim 1, characterized in that: After acquiring the satellite signal, the satellite signal receiver divides it into two channels: an in-line signal and a quadrature signal. The in-line and quadrature signals are first mixed and multiplied with the carrier generated by the local carrier generator through a carrier loop. In the in-line channel, the signals are multiplied with a sine carrier generated by the carrier generator based on a sine table, while in the quadrature channel, the signals are multiplied with a cosine carrier generated by the carrier generator based on a cosine table. This allows carrier stripping of the in-line and quadrature channels, respectively. Three correlators, namely, advance, immediate and lag, are set in the co-directional channel and the orthogonal channel respectively; in the co-directional channel of the code tracking loop, the three C / A codes, namely advance, immediate and lag, generated by the code generator are correlated with the co-directional signal after carrier stripping and passed through an integrator-scavenger to obtain the advance, immediate and lag correlation values; similarly, in the orthogonal channel, the orthogonal signal is correlated with the three C / A codes and integrated to obtain the advance, immediate and lag correlation values.

10. A terminal device comprising a processor, a memory, and a computer program stored in the memory; characterized in that: When the processor executes the computer program, it implements the satellite navigation signal spoofing detection method according to any one of claims 1 to 9.

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