A method, apparatus and medium for detecting GNSS spoofing interference

Abstract

This application relates to the field of satellite network security, and in particular to a GNSS spoofing interference detection method, device, and medium. The method calculates the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observations; accumulates the detection statistics of the nth satellite at a single moment according to a preset cumulative length to generate a cumulative detection statistics for the nth satellite; and determines whether the nth satellite is subject to interference spoofing based on the cumulative detection statistics. This method can be directly applied to existing commercial GNSS receivers, achieving fast and effective spoofing interference detection without requiring additional hardware or modifications to the receiver hardware, thus preventing the user's location, time, and other information from being spoofed.

Description

Technical Field

[0001] This application relates to the field of satellite network security, and in particular to a GNSS deception interference detection method, device and medium. Background Technology

[0002] GNSS (Global Navigation Satellite System) spoofing interference detection technology is one of the key technologies for ensuring the safe application of satellite navigation systems. With the widespread application of satellite navigation technology in fields such as transportation, communication, power, finance, aviation, and aerospace, spoofing interference has become a serious security threat. GNSS spoofing interference detection has wide applications and urgent needs in civil aviation, intelligent transportation, and autonomous driving. Current GNSS spoofing interference detection methods are generally based on internal parameters of each satellite tracking channel, such as signal quality management (SQM), power detection, Doppler detection, and autonomous integrity detection. Typically, relevant GNSS parameters are selected for monitoring. First, relevant parameter data is collected in real time, and the characteristics of signal strength, frequency, and phase are analyzed and compared with normal signals to identify possible abnormal features, such as abnormal changes in signal strength or frequency shifts. A detection threshold is calculated based on the probability distribution of normal signal parameters. Then, by comparing the abnormal features in the signal, spoofing interference is considered to exist when the parameter characteristics exceed the threshold.

[0003] However, existing GNSS spoofing interference detection techniques have the following drawbacks: Because the parameters required by existing GNSS spoofing interference detection methods are not considered in the receiver design, the required parameters cannot be directly extracted, necessitating modifications to the receiver's hardware structure or the addition of extra equipment to achieve GNSS spoofing interference; because existing GNSS spoofing interference detection methods have a small detection window and low sensitivity to detection parameters, they require high-rate data and lack sufficient detection performance for low-rate data (e.g., 1Hz); and because existing GNSS spoofing interference detection methods only use feature values ​​from the current or past period, the detection speed is not fast enough.

[0004] Therefore, how to directly implement GNSS deception and interference on existing commercial GNSS receivers is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a GNSS spoofing interference detection method that can achieve high detection accuracy and high detection speed on existing commercial GNSS receivers without adding extra hardware or changing the receiver hardware.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] In a first aspect, the present invention provides a GNSS spoofing interference detection method, applied to a GNSS receiver, comprising:

[0008] Acquire the GNSS satellite signals received by the receiver, and extract the pseudorange observations, on-orbit motion status, and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals;

[0009] Calculate the relative acceleration between the GNSS receiver and the nth satellite based on the current on-orbit motion state of the nth satellite;

[0010] Based on the satellite frequency drift, relative acceleration, and pseudorange observation of the nth satellite, calculate the detection statistics of the nth satellite at a single moment;

[0011] The cumulative detection statistics of the nth satellite are generated by accumulating the detection statistics of the nth satellite at a single moment according to the preset cumulative length.

[0012] The presence of interference or deception by the nth satellite is determined based on the cumulative detection statistics of the nth satellite.

[0013] In a preferred embodiment of this application, the step of calculating the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observation of the nth satellite includes:

[0014] Define the pseudorange observation of the nth satellite as ρ n [k], the relative acceleration between the GNSS receiver and the nth satellite is The frequency drift of the nth satellite is The detection statistics of the nth satellite at a single moment are T. n [k], then:

[0015]

[0016] in, is the second-order difference symbol, Δt is the sampling interval, and c is the speed of light.

[0017] In a preferred embodiment of this application, the step of accumulating the detection statistics of the nth satellite at a single moment according to a preset cumulative length to generate the cumulative detection statistics of the nth satellite includes:

[0018]

[0019] Where L is the cumulative length, This represents the cumulative detection statistics.

[0020] In a preferred example of this application, it can be further configured to include calculating a threshold γ, the process of which includes:

[0021] Preset false alarm rate P FA Calculate the frequency drift noise of the user over a previous period of time. and second-order pseudorange measurement noise and The sum of the pseudorange observations ρ from the nth satellite n [k] is obtained from the measurement noise;

[0022] The threshold γ initial value is calculated based on data collected within a time period K seconds after the receiver is powered on, combined with the threshold calculation formula. The threshold calculation formula is as follows:

[0023]

[0024] Among them, Q -1 Let K be the right-tail probability function of the chi-square distribution, where K equals the cumulative length.

[0025] The threshold γ is updated every K seconds, and the updated γ value is calculated using the data collected in the previous K seconds combined with the threshold calculation formula.

[0026] In a preferred embodiment of this application, the step of determining whether the nth satellite is subject to interference or spoofing based on the cumulative detection statistics of the nth satellite includes:

[0027] Based on the cumulative detection statistics of the nth satellite calculated in real time The value of the threshold γ is used to determine whether the nth satellite is subject to GNSS deception interference.

[0028] In a preferred example of this application, it may further be configured to include:

[0029] If the nth satellite is determined to be free from interference or deception, receiver positioning and timing calculations will be performed on the signal from this satellite; otherwise, receiver positioning and timing calculations will be prohibited on the signal from this satellite.

[0030] Secondly, this application provides a GNSS spoofing interference detection device, the device comprising:

[0031] The data acquisition module is used to acquire GNSS satellite signals received by the receiver and extract pseudorange observations, on-orbit motion status, and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals.

[0032] The detection statistics module is used to calculate the relative acceleration between the GNSS receiver and the nth satellite based on the on-orbit motion state of the nth satellite at the current moment; and to calculate the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observation of the nth satellite.

[0033] The cumulative detection statistics module is used to accumulate the detection statistics of the nth satellite at a single moment according to a preset cumulative length, and generate the cumulative detection statistics of the nth satellite.

[0034] The judgment module is used to determine whether the nth satellite is subject to interference or deception based on the cumulative detection statistics of the nth satellite.

[0035] Thirdly, this application provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the GNSS spoofing interference detection method as described in any of the preceding claims.

[0036] Fourthly, this application provides a computer-readable storage medium storing a program, wherein when the program is executed by a processor, it implements the GNSS spoofing interference detection method as described in any of the preceding claims.

[0037] Fifthly, this application provides a computer program product including computer instructions that, when executed by a processor, implement the steps of the GNSS spoofing interference detection method as described in any of the preceding claims.

[0038] In summary, compared with the prior art, the beneficial effects of the technical solution provided by the embodiments of this application include at least the following: it can be directly applied to existing commercial GNSS receivers to achieve fast and effective spoofing interference detection, without adding extra hardware or changing receiver hardware on commercial GNSS receivers, thus preventing users' location, time and other information from being spoofed. Attached Figure Description

[0039] Figure 1 This is a flowchart of a GNSS spoofing interference detection method provided in one embodiment of this application.

[0040] Figure 2 This is a structural diagram of a GNSS spoofing interference detection device provided in one embodiment of this application. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0042] In one embodiment of this application, a GNSS spoofing interference detection method is provided. Please refer to [link / reference]. Figure 1 As shown, the method includes:

[0043] S100: Acquire the GNSS satellite signals received by the receiver, and extract the pseudorange observations, on-orbit motion status, and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals.

[0044] Specifically, the GNSS (Global Navigation Satellite System) receiver is a commercial GNSS receiver.

[0045] S200: Calculate the relative acceleration between the GNSS receiver and the nth satellite based on the current on-orbit motion state of the nth satellite.

[0046] S300: Calculate the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observation of the nth satellite.

[0047] In a preferred embodiment, calculating the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observations of the nth satellite includes:

[0048] Define the pseudorange observation of the nth satellite as ρ n [k], the relative acceleration between the GNSS receiver and the nth satellite is The frequency drift of the nth satellite is The detection statistics of the nth satellite at a single moment are T. n [k], then:

[0049]

[0050] in, is the second-order difference symbol, Δt is the sampling interval, and c is the speed of light.

[0051] S400: Accumulate the detection statistics of the nth satellite at a single moment according to the preset cumulative length to generate the cumulative detection statistics of the nth satellite.

[0052] In a preferred embodiment, the step of accumulating the detection statistics of the nth satellite at a single moment according to a preset cumulative length to generate the cumulative detection statistics of the nth satellite includes:

[0053]

[0054] Where L is the cumulative length, This represents the cumulative detection statistics.

[0055] Specifically, the preset cumulative length is the cumulative length set by the user.

[0056] S500: Determine whether the nth satellite is subject to interference or deception based on the cumulative detection statistics of the nth satellite.

[0057] In a preferred embodiment, the method further includes calculating a threshold γ, the process of which includes:

[0058] Preset false alarm rate P FA Calculate the frequency drift noise of the user over a previous period of time. and second-order pseudorange measurement noise and The sum of the pseudorange observations ρ from the nth satellite n [k] is obtained from the measurement noise;

[0059] The threshold γ initial value is calculated based on data collected within a time period K seconds after the receiver is powered on, combined with the threshold calculation formula. The threshold calculation formula is as follows:

[0060]

[0061] Among them, Q -1 Let K be the right-tail probability function of the chi-square distribution, where K equals the cumulative length.

[0062] The threshold γ is updated every K seconds, and the updated γ value is calculated using the data collected in the previous K seconds combined with the threshold calculation formula.

[0063] Specifically, the threshold is calculated using historical data. After obtaining the threshold value, the cumulative detection statistics of the nth satellite are calculated in real time. The value of the threshold γ is used to determine whether the nth satellite is subject to GNSS deception interference.

[0064] In this embodiment, the method is a software that can be directly applied to existing commercial GNSS receivers to achieve fast and effective spoofing interference detection without adding extra hardware or changing the receiver hardware on commercial GNSS receivers, thus preventing users' location, time, and other information from being spoofed.

[0065] In some embodiments, it also includes:

[0066] If the nth satellite is determined to be free from interference or deception, receiver positioning and timing calculations will be performed on the signal from this satellite; otherwise, receiver positioning and timing calculations will be prohibited on the signal from this satellite.

[0067] In practice, when calculating the receiver position and time (positioning and timing), based on the judgment result of interference spoofing, satellite groups with abnormal signals, i.e., those involved in interference spoofing, are excluded, and their relevant information is not used for calculation.

[0068] In this embodiment, the problem of positioning and timing deviation exceeding the user's acceptable range before the detection of spoofing signals is avoided, and the ability to continue providing normal positioning and timing is provided even in the event of spoofing interference is ensured.

[0069] This application also provides a GNSS spoofing interference detection device; please refer to [link / reference]. Figure 2 As shown, the device includes:

[0070] The data acquisition module 100 is used to acquire GNSS satellite signals received by the receiver and extract pseudorange observations, on-orbit motion status and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals.

[0071] The detection statistics module 200 is used to calculate the relative acceleration between the GNSS receiver and the nth satellite based on the on-orbit motion state of the nth satellite at the current moment; and to calculate the detection statistics of the nth satellite at a single moment based on the satellite frequency drift, relative acceleration, and pseudorange observation of the nth satellite.

[0072] The cumulative detection statistics module 300 is used to accumulate the detection statistics of the nth satellite at a single moment according to a preset cumulative length, and generate the cumulative detection statistics of the nth satellite.

[0073] The judgment module 400 is used to determine whether the nth satellite is subject to interference or deception based on the cumulative detection statistics of the nth satellite.

[0074] The functions of each module in the above-mentioned GNSS deception interference detection device correspond to the steps in the above-mentioned GNSS deception interference detection method embodiment, and their functions and implementation processes will not be described in detail here.

[0075] This application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the GNSS spoofing interference detection method as described in any of the above embodiments.

[0076] This application also provides a computer-readable storage medium storing a program. The computer-readable storage medium refers to a data storage medium, which may include, but is not limited to, floppy disks, optical disks, hard disks, flash memory, USB flash drives, and / or Memory Sticks. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The working process, details, and technical effects of the computer-readable storage medium provided in this embodiment can be found in the above embodiment regarding a GNSS spoofing interference detection method, and will not be repeated here.

[0077] The application also provides a computer program product, including computer instructions that, when executed by a processor, implement the steps of the GNSS spoofing interference detection method as described in any of the above embodiments.

[0078] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM).

[0079] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. The above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that for those skilled in the art, several modifications and improvements can be made without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for detecting GNSS spoofing interference, characterized in that, Applications in GNSS receivers include: Acquire the GNSS satellite signals received by the receiver, and extract the pseudorange observations, on-orbit motion status, and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals; Calculate the relative acceleration between the GNSS receiver and the nth satellite based on the current on-orbit motion state of the nth satellite; Define the pseudorange observation of the nth satellite as The relative acceleration between the GNSS receiver and the nth satellite is The frequency drift of the nth satellite is The detection statistics of the nth satellite at a single moment are ,but: ； in, The sign for the second-order difference is... Sampling interval, The speed of light; The cumulative detection statistics of the nth satellite are generated by summing the detection statistics of the nth satellite at a single moment according to a preset cumulative length, using the following formula: ； Where L is the cumulative length, This represents the cumulative detection statistics; The presence of interference or deception by the nth satellite is determined based on the cumulative detection statistics of the nth satellite.

2. The GNSS spoofing interference detection method according to claim 1, characterized in that, It also includes calculating the threshold. The process includes: Preset false alarm rate Calculate the frequency drift noise of the user over a previous period of time. and second-order pseudorange measurement noise , and The sum of the pseudorange observations from the nth satellite The noise was obtained from the measurement; Threshold The initial value is based on the length of time since the receiver was powered on. The threshold is calculated by combining the data within a second with the threshold calculation formula, which is: ； in, Let be the right-tail probability function of the chi-square distribution. Equal to the cumulative length; Let the threshold Every Updated every second. The value is calculated using the data collected in the previous K seconds combined with the threshold calculation formula.

3. The GNSS spoofing interference detection method according to claim 2, characterized in that, The step of determining whether the nth satellite is subject to interference or deception based on the cumulative detection statistics of the nth satellite includes: Based on the cumulative detection statistics of the nth satellite calculated in real time With the threshold The size of the first [item] determines the [number]th [item]. Does the satellite exhibit GNSS deception or interference? 4. The GNSS spoofing interference detection method according to claim 3, characterized in that, Also includes: If the nth satellite is determined to be free from interference or deception, receiver positioning and timing calculations will be performed on the signal from this satellite; otherwise, receiver positioning and timing calculations will be prohibited on the signal from this satellite.

5. A GNSS spoofing interference detection device, characterized in that, include: The data acquisition module is used to acquire GNSS satellite signals received by the receiver and extract pseudorange observations, on-orbit motion status, and satellite frequency drift of all visible satellites at the current time from the GNSS satellite signals. The detection statistics module is used to define the pseudorange observations of the nth satellite as follows. The relative acceleration between the GNSS receiver and the nth satellite is The frequency drift of the nth satellite is The detection statistics of the nth satellite at a single moment are ,but: ； in, The sign for the second-order difference is... Sampling interval, The speed of light; Based on the satellite frequency drift, relative acceleration, and pseudorange observations of the nth satellite, the detection statistics for the nth satellite at a single moment are calculated using the following formula: ； Where L is the cumulative length, This represents the cumulative detection statistics; The cumulative detection statistics module is used to accumulate the detection statistics of the nth satellite at a single moment according to a preset cumulative length, and generate the cumulative detection statistics of the nth satellite. The judgment module is used to determine whether the nth satellite is subject to interference or deception based on the cumulative detection statistics of the nth satellite.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the GNSS spoofing interference detection method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program, wherein when the program is executed by a processor, it implements the GNSS spoofing interference detection method as described in any one of claims 1 to 4.

8. A computer program product comprising computer instructions, characterized in that, When executed by a processor, the computer instructions implement the steps of the GNSS spoofing interference detection method according to any one of claims 1 to 4.

Images