Satellite navigation deception detection method, device and equipment based on total electron number deviation and storage medium

Abstract

The invention provides a satellite navigation deception detection method, device and equipment based on total electron number deviation and a storage medium, and relates to the technical field of satellite navigation. The method comprises the following steps: acquiring a satellite signal of each satellite, and preprocessing the satellite signal to obtain a dual-frequency original pseudo-range observed quantity corresponding to the satellite signal; determining a total electron number measurement value of each satellite based on the double-frequency original pseudo-range observed quantity; global ionosphere map grid information is acquired, and a total electron number reference value of each satellite is determined based on the global ionosphere map grid information; determining a detection statistic of each satellite based on the total electron number measurement value and the total electron number reference value; and judging whether the satellite signal of each corresponding satellite is a deception signal or not based on the detection statistic and the deception detection threshold value of each satellite. According to the embodiment of the invention, whether the satellite signal is the deception signal can be accurately detected, and the deception jamming detection capability of the double-frequency GNSS receiver is improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation technology, and in particular to a satellite navigation deception detection method, device, equipment and storage medium based on total electronic number deviation. Background Art

[0002] The Global Navigation Satellite System (GNSS), including the US Global Positioning System (GPS), the Russian Global Navigation Satellite System (GLONASS), the EU Galileo Satellite Navigation System (Galileo), and China's Beidou Satellite Navigation System (BDS), can provide users with all-weather, all-day navigation, positioning and timing services. It has been widely used in scenarios such as intelligent transportation, unmanned equipment, energy and electricity, communication facilities and meteorological monitoring. The related industries have high economic value and broad market prospects.

[0003] However, in recent years, there have been a large number of publicized GNSS spoofing and jamming incidents, raising concerns about the security and reliability of the services it provides. GNSS spoofers forge GNSS signals to induce the target receiver to output false positioning, velocity and timing (PVT) results.

[0004] Among the GNSS spoofing incidents that have occurred so far, generative spoofing is a relatively mainstream low-cost spoofing solution: the spoofer uses methods including GNSS signal simulators and software-defined radio (SDR) to directly broadcast a set of GNSS signals corresponding to their expected PVT results. At this time, because the signals designed by the spoofer have good PVT information self-consistency, the existing traditional anti-spoofing methods based on verification of redundant information between signals are often difficult to work.

[0005] Therefore, how to detect whether a satellite signal is a spoofing signal is a technical problem that needs to be solved urgently. Summary of the invention

[0006] The present invention provides a satellite navigation deception detection method, device, equipment and storage medium based on total electron number deviation, which can accurately detect whether a satellite signal is a deception signal and improve the deception interference detection capability of a dual-frequency GNSS receiver.

[0007] In a first aspect, the present invention provides a satellite navigation spoofing detection method based on total electron number deviation, comprising the following steps: Acquire a satellite signal of each satellite, and preprocess the satellite signal to obtain a dual-frequency original pseudo-range observation corresponding to the satellite signal; Determine a total electron count measurement value of each satellite based on the dual-frequency raw pseudorange observations; Obtain the global ionospheric map grid information, and based on the global ionospheric map grid information, determine the reference value of the total electron content for each satellite; Based on the measured value of the total electron content and the reference value of the total electron content, determine the detection statistic for each satellite; Based on the detection statistic of each satellite and the spoofing detection threshold, determine whether the satellite signal corresponding to each satellite is a spoofing signal.

[0008] Preferably, according to a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, the preprocessing of the satellite signal to obtain the dual-frequency raw pseudorange observation corresponding to the satellite signal includes: Perform a first rule process on the satellite signal to obtain the corresponding digital intermediate frequency signal; Perform a second rule process on the digital intermediate frequency signal to obtain the dual-frequency raw pseudorange observation corresponding to the satellite signal; Wherein, the first rule process at least includes low-noise amplification, down-conversion, and analog-to-digital conversion processing, and the second rule process at least includes acquisition, tracking, and message demodulation processing.

[0009] Preferably, according to a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, the determining the reference value of the total electron content for each satellite based on the global ionospheric map grid information includes: According to the preset position information of the receiver, calculate the longitude and latitude of the ionospheric piercing point of each satellite to the receiver; Based on the global ionospheric map grid information and the longitude and latitude of the ionospheric piercing point, calculate the real-time vertical total electron content reference value and the corresponding vertical uncertainty of the corresponding piercing point; Based on the real-time vertical total electron content reference value, the vertical uncertainty, and the single-layer spherical shell model, calculate the reference value of the total electron content on the actual satellite signal propagation path and the corresponding target uncertainty.

[0010] Preferably, according to a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, while determining the measured value of the total electron content for each satellite based on the dual-frequency raw pseudorange observation, calculate the variance value corresponding to the measured value of the total electron content; The method for determining the detection statistic for each satellite based on the measured value of the total electron content and the reference value of the total electron content includes: Based on the measured value of the total electron content, the reference value of the total electron content, the variance value, and the target uncertainty, calculate the detection statistic for each satellite.

[0011] Preferably, for a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, the step of determining the spoofing detection threshold includes: Obtain a preset false probability; Calculate the false probability and the inverse function of the Gaussian right-tail function to obtain the spoofing detection threshold.

[0012] Preferably, for a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, determining whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic and the spoofing detection threshold of each satellite includes: If the absolute value of the detection statistic of the satellite is greater than the spoofing detection threshold, determine that the satellite signal of the corresponding satellite is a spoofing signal; If the absolute value of the detection statistic of the satellite is less than or equal to the spoofing detection threshold, determine that the satellite signal of the corresponding satellite is a genuine signal.

[0013] In a second aspect, the present invention further provides a satellite navigation spoofing detection device based on the total electron content deviation, including the following modules: A preprocessing module, configured to obtain the satellite signal of each satellite and preprocess the satellite signal to obtain a dual-frequency raw pseudorange measurement corresponding to the satellite signal; A total electron content measurement value determination module, configured to determine the total electron content measurement value of each satellite based on the dual-frequency raw pseudorange measurement; A total electron content reference value determination module, configured to obtain global ionospheric map grid information and determine the total electron content reference value of each satellite based on the global ionospheric map grid information; A detection statistic determination module, configured to determine the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; A spoofing signal judgment module, configured to determine whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic and the spoofing detection threshold of each satellite.

[0014] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the satellite navigation spoofing detection method based on the total electron content deviation as described in any one of the above.

[0015] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the satellite navigation spoofing detection method based on the total electron content deviation as described in any one of the above.

[0016] Fifth aspect, the present invention further provides a computer program product, including a computer program which, when executed by a processor, implements the satellite navigation spoofing detection method based on total electron content deviation as described in any one of the above.

[0017] A satellite navigation spoofing detection method, device, equipment and storage medium based on total electron content deviation provided by the present invention obtain satellite signals of each satellite, preprocess the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; determine the total electron content measurement values of each satellite based on the dual-frequency raw pseudorange observables; obtain global ionospheric map grid information, and determine the total electron content reference values of each satellite based on the global ionospheric map grid information; determine the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; and determine whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic of each satellite and the spoofing detection threshold. It can accurately detect whether the satellite signal is a spoofing signal and improve the spoofing interference detection ability of the dual-frequency GNSS receiver. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1 is one of the flow diagrams of the satellite navigation spoofing detection method based on total electron content deviation provided by the present invention.

[0020] Figure 2 is the second flow diagram of the satellite navigation spoofing detection method based on total electron content deviation provided by the present invention.

[0021] Figure 3 is the schematic diagram of the simulation source experimental scenario provided by the present invention.

[0022] Figure 4 is the schematic diagram of the absolute value of the detection statistic of each spoofing signal varying with time under full-channel spoofing provided by the present invention.

[0023] Figure 5 is the schematic diagram of comparing the absolute value of the difference between the TEC measurement value and the TEC reference value of each signal at a single moment with the spoofing detection threshold provided by the present invention.

[0024] Figure 6 is the schematic diagram of the structure of the satellite navigation spoofing detection device based on total electron content deviation provided by the present invention.

[0025] Figure 7 It is a schematic structural diagram of the electronic device provided by the present invention. Detailed implementation manners

[0026] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0027] First, several terms involved in the present invention are analyzed: Total Electron Content (TEC): It is a key parameter in ionospheric research, representing the total number of free electrons in a column with a unit area along a specific path (such as the satellite signal propagation path). TEC refers to the total number of free electrons in a cross-section of one square meter along a vertical or oblique path from the Earth's surface to a satellite (or a certain altitude).

[0028] Global Ionospheric Map (abbreviated as GIM): It is a two-dimensional or three-dimensional image used to represent the distribution of the total electron content in the ionosphere of the Earth's upper atmosphere. The data of GIM mainly comes from Global Navigation Satellite Systems (GNSS), such as GPS, GLONASS, Galileo, Beidou, etc. When these satellites orbit the Earth, they emit signals. When the signals pass through the ionosphere, they interact with the free electrons in the ionosphere, resulting in changes in the propagation speed and direction of the signals. By receiving these satellite signals and analyzing their delays and changes, the total electron content (TEC) in the ionosphere can be calculated, thereby constructing the global ionospheric map.

[0029] Global Navigation Satellite System (GNSS): It is a space-based radio navigation and positioning system that can provide users at any location on the Earth's surface or in near-Earth space with all-weather 3D coordinates, speed, and time information. Its positioning principle is based on the concept of trilateration, and it accurately determines its own position by measuring the distances to four or more satellites. Each satellite transmits a signal to the ground. When the signal reaches the receiver, the receiver can know the time it takes for the satellite signal to reach here. The signal propagation speed is the fixed speed of light. By multiplying the signal propagation time by the speed of light, the distance from the receiver to the satellite, which is the radius of the first sphere, can be obtained. The intersection of three spheres is a ring, and adding a fourth sphere can determine the accurate position of the receiver and correct the clock error of the receiver to determine the correct time.

[0030] BeiDou Navigation Satellite System (BDS): It is China's BeiDou satellite navigation system, a global satellite navigation system independently built and operated by China, which can provide all-weather, all-time, and high-precision positioning, navigation, and timing services for global users. It has various characteristic functions such as short message communication and satellite-based augmentation.

[0031] Positioning, Velocity, and Timing (PVT): It refers to the service of providing accurate position, speed, and time information through a satellite navigation system. PVT is the abbreviation of Position, Velocity, and Time, which allows users to determine their position, speed, and current time in three-dimensional space.

[0032] GNSS spoofing event: It refers to sending false GNSS signals to deceive the receiver, causing it to calculate incorrect PVT (position, speed, and time) results. Such spoofing behavior may lead to serious safety consequences, especially in those fields that rely on GNSS for critical operations.

[0033] In the related technologies, there are at least the following technical problems: In the currently occurred GNSS spoofing events, generative spoofing is a relatively mainstream low-cost spoofing scheme: The spoofing party uses methods including GNSS signal simulators and software-defined radios (SDRs) to directly broadcast a set of GNSS signals corresponding to its expected PVT results. At this time, due to the good PVT information self-consistency within the signals designed by the spoofing party, the existing traditional anti-spoofing methods based on redundant information between signals often fail to work.

[0034] However, as low-cost signal generation devices, most current generative spoofing sources usually have difficulty directly obtaining real-time ionospheric information of the spoofing location from the network, and it is also difficult to accurately modulate this information into the GNSS signals they broadcast, so that the forged GNSS signals have the same ionospheric effect as the real GNSS signals at that location. On the other hand, with the widespread application of dual-frequency GNSS receivers in various scenarios, a large number of satellite navigation receivers can now obtain dual-frequency pseudorange measurements of the same or multiple GNSS systems. At the same time, a large number of dual-frequency GNSS application scenarios, such as mobile intelligent terminals, intelligent connected vehicles, communication base stations, etc., can also access the Internet simultaneously, and then obtain ionospheric reference information such as real-time or quasi-real-time global ionospheric maps (GIM) from public websites and various GNSS service providers.

[0035] Based on the above facts, taking advantage of the differences in real-time ionospheric information acquisition between current generative spoofing sources and receivers, the following combines Figures 1 - 7 to describe a satellite navigation spoofing detection method, device, equipment and storage medium based on the total electron content deviation of the present invention. This method calculates the TEC on the propagation path from the satellite to the receiver using the dual-frequency pseudorange observables extracted from the same satellite signal by a dual-frequency GNSS receiver, and then compares it with the TEC reference value calculated from the GIM grid data from the network service to check whether there is an abnormality in the ionospheric information contained in the satellite signal, that is, to detect whether the corresponding signal is a spoofing signal.

[0036] Thus, the embodiments provided by the present invention can significantly increase the cost of generative spoofing sources launching spoofing attacks on network-connected dual-frequency GNSS receivers, thereby enhancing the anti-spoofing ability of the latter. At the same time, since the embodiments provided by the present invention can perform reliability verification for each channel, they can provide channel-level spoofing detection for GNSS receivers when real and spoofed GNSS signals coexist, that is, they can exclude spoofing signals and select real signals, and then provide correct PVT results for users.

[0037] In summary, a satellite navigation spoofing detection method, device, equipment and storage medium based on the total electron content deviation proposed by the present invention can be applied to detect generative full-channel dual-frequency spoofing; generally, this satellite navigation spoofing detection method based on the total electron content deviation is also applicable to detecting single-frequency generative spoofing or single-frequency retransmitted spoofing. The obtained channel-level spoofing detection results can either directly issue spoofing warnings to the upper-layer system or users, or be used to exclude spoofing signals and select real signals, and then provide correct PVT results for users.

[0038] Figure 1 is one of the flow schematic diagrams of a satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention, as Figure 1As shown, the method may include but is not limited to steps S100 to S500: S100, obtaining satellite signals of each satellite and preprocessing the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; S200, determining total electron content measurement values of each satellite based on the dual-frequency raw pseudorange observables; S300, obtaining global ionospheric map grid information and determining total electron content reference values of each satellite based on the global ionospheric map grid information; S400, determining detection statistics of each satellite based on the total electron content measurement values and the total electron content reference values; S500, determining whether the satellite signals of each corresponding satellite are spoofing signals based on the detection statistics of each satellite and a spoofing detection threshold.

[0039] In step S100 of some embodiments, satellite signals of each satellite are obtained and the satellite signals are preprocessed to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals.

[0040] It can be understood that a GNSS antenna is a device for receiving signals of the Global Navigation Satellite System (GNSS). The GNSS antenna receives signals transmitted by satellites, i.e., satellite signals, which are transmitted to the Earth's surface in the form of electromagnetic waves. The GNSS antenna not only needs to receive these signals but also needs to decode them to determine the precise position of the receiver.

[0041] When satellite signals transmitted by multiple satellites are received using a GNSS antenna, a computer system is used to obtain the satellite signals transmitted by each satellite.

[0042] It should be noted that the step of preprocessing the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals specifically includes: performing a first rule process on the satellite signals to obtain corresponding digital intermediate frequency signals; performing a second rule process on the digital intermediate frequency signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; wherein the first rule process at least includes low-noise amplification, down-conversion, and analog-to-digital conversion processing, and the second rule process at least includes acquisition, tracking, and message demodulation processing.

[0043] Specifically, that is, performing low-noise amplification processing, down-conversion processing, and analog-to-digital conversion processing on the satellite signals transmitted by each satellite in sequence to obtain dual-frequency raw pseudorange observables corresponding to each satellite signal.

[0044] Purpose of Low-Noise Amplification (LNA): Amplify weak satellite signals and suppress system noise.

[0045] Purpose of Downconversion: Convert high-frequency GNSS signals into intermediate-frequency (IF) signals for subsequent processing.

[0046] Purpose of Analog-to-Digital Conversion (ADC): Convert analog intermediate-frequency signals into digital intermediate-frequency signals.

[0047] After processing through the first rule to obtain the digital intermediate-frequency signal, perform acquisition, tracking, and message demodulation processing on the digital intermediate-frequency signal in sequence to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals, and extract the dual-frequency pseudorange observables of each satellite signal , with the unit of meter (m). Among them, and represent the satellite serial number and the frequency point serial number respectively, represents the total number of satellite channels.

[0048] Through acquisition, tracking, and demodulation processing, the dual-frequency GNSS receiver can output high-precision pseudorange observables. Combining with the dual-frequency ionospheric correction technology, the single-point positioning error can be compressed from the meter level to the sub-meter level, laying a foundation for high-precision navigation and positioning. In actual implementation, algorithm optimization needs to be carried out for signal strength, dynamic environment, and multipath interference, and the hardware deviation of the receiver needs to be calibrated.

[0049] In step S200 of some embodiments, based on the dual-frequency raw pseudorange observables, determine the total electron content measurement value of each satellite.

[0050] It can be understood that after executing the steps of step S100, the specific execution steps can be to calculate the dual-frequency raw pseudorange observables, and the total electron content measurement value of each satellite can be obtained.

[0051] It should be noted that while determining the total electron content measurement value of each satellite based on the dual-frequency raw pseudorange observables, calculate the variance value corresponding to the total electron content measurement value; Furthermore, the steps of calculating the TEC measurement value (total electron content measurement value) of the th satellite are as follows in formula (1), and the steps of calculating the variance value corresponding to the TEC measurement value (total electron content measurement value) are as follows in formula (2): (1) (2) Where is the first-order Taylor expansion of the ionospheric refraction coefficient, generally taking ; is the carrier emission frequency of the GNSS signal at the frequency point , with the unit of Hertz (Hz); is the hardware delay difference between the two frequencies of the receiver, with the unit of second (s); is the th satellite's hardware delay difference between the two frequencies, with the unit of second (s); is the propagation speed of radio waves, i.e., the speed of light, generally taking ; is the th satellite's variance of the part unrelated to the frequency point in the pseudorange observation noise of the satellite, with the unit of .

[0052] In step S300 of some embodiments, global ionospheric map grid information is obtained, and based on the global ionospheric map grid information, the total electron content reference value of each satellite is determined.

[0053] It can be understood that after the steps of step S200 are executed, the specific execution steps may be: first, global ionospheric map grid information is obtained.

[0054] Then, according to the preset position information of the receiver, the longitude and latitude of the ionospheric pierce point of each satellite to the receiver are calculated; Based on the global ionospheric map grid information and the longitude and latitude of the ionospheric pierce point, the real-time vertical total electron content reference value and the corresponding vertical uncertainty of the corresponding pierce point are calculated; Based on the real-time vertical total electron content reference value, the vertical uncertainty and the single-layer spherical shell model, the total electron content reference value on the actual satellite signal propagation path and the corresponding target uncertainty are calculated.

[0055] Among them, to obtain the global ionospheric map grid information, the GIM grid information (global ionospheric map grid information) is obtained from other GIM sources such as the International GNSS Service (IGS) website.

[0056] Then, according to the rough position information of the receiver, the longitude and latitude of the ionospheric pierce point of the th satellite to the receiver are calculated by a conventional method, and then interpolation calculations in the time dimension and the space dimension are performed on the GIM grid and its corresponding root mean square error (RMS) grid to obtain the real-time vertical TEC (VTEC) reference value (real-time vertical total electron content reference value) and its uncertainty (vertical uncertainty) at the corresponding pierce point.

[0057] Based on the real-time vertical total electron content reference value, the vertical uncertainty, and the single-layer spherical shell model (SLM), the reference value of the total electron content on the actual satellite signal propagation path and the corresponding target uncertainty can be calculated as follows: According to and , the steps to estimate the TEC reference value (reference value of the total electron content) on the actual satellite signal propagation path and the uncertainty (target uncertainty) corresponding to the TEC reference value (reference value of the total electron content) using the single-layer spherical shell model (SLM) are as shown in formula (3) below: (3) where is the real-time vertical total electron content reference value, is the vertical uncertainty, is the equivalent elevation angle of the th satellite, which can be calculated using the actual satellite elevation angle as follows: (4) where is the radius of the Earth, is the equivalent ionospheric height.

[0058] In step S400 of some embodiments, based on the total electron content measurement value and the total electron content reference value, the detection statistic of each satellite is determined.

[0059] It can be understood that after the steps of step S300 are executed, the specific execution steps can be: based on the total electron content measurement value, the total electron content reference value, the variance value, and the target uncertainty, calculate the detection statistic of each satellite. The steps to calculate the detection statistic of the th satellite are as shown in formula (5) below: (5) where is the detection statistic, is the TEC measurement value of the th satellite, is the TEC reference value (reference value of the total electron content), is the variance value corresponding to the TEC measurement value (total electron content measurement value), is the uncertainty (target uncertainty) corresponding to the TEC reference value.

[0060] In step S500 of some embodiments, based on the detection statistic of each satellite and the spoofing detection threshold, it is determined whether the satellite signal of each corresponding satellite is a spoofing signal.

[0061] It should be noted that the deception detection threshold is first determined. The specific steps for determining the deception detection threshold include: Obtain a preset false probability; Calculate the false probability and the inverse function of the Gaussian right-tail function to obtain the deception detection threshold.

[0062] In some embodiments, the steps for calculating the deception detection threshold are shown in the following formula (6): According to the false alarm probability given by the user , calculate the corresponding deception detection threshold according to the following formula (6) : (6) Where represents the inverse function of the following Gaussian right-tail function : (7) In some embodiments of the present invention, based on the detection statistic and the deception detection threshold of each satellite, determining whether the satellite signal of each corresponding satellite is a spoofing signal specifically includes: If the absolute value of the detection statistic of the satellite is greater than the deception detection threshold, determine that the satellite signal of the corresponding satellite is a spoofing signal; If the absolute value of the detection statistic of the satellite is less than or equal to the deception detection threshold, determine that the satellite signal of the corresponding satellite is a genuine signal.

[0063] If the absolute value of the detection statistic of the th satellite calculated using formula (5) is greater than the deception detection threshold calculated using formula (6), determine that the satellite signal of the current th satellite is a spoofing signal, and initiate a spoofing alarm to the user.

[0064] Otherwise, if the absolute value of the detection statistic of the satellite is less than or equal to the deception detection threshold, the satellite signal of the th satellite is determined to be a genuine signal, and jump to the step corresponding to formula (1), and then repeat the steps corresponding to formulas (1) to (7) to perform spoofing detection on the remaining satellite signals that have not been spoofing detected until all channel satellite signals are traversed.

[0065] Through the above embodiments, the present invention can accurately detect whether a satellite signal is a spoofing signal and improve the spoofing interference detection ability of a dual-frequency GNSS receiver.

[0066] Figure 2This is the second process schematic diagram of the satellite navigation spoofing detection method based on the total electron content deviation provided by the present invention. In this embodiment, taking the BDS civilian B1I and B3I signals as examples, the implementation steps of the present invention are demonstrated. The implementation of the method of the present invention is not limited to a specific navigation system, the selected dual-frequency signals or satellite PRNs, and the detector parameter configuration can also be configured according to user requirements. The signal configuration for testing is as follows: The spoofing source simulates the signals of a total of 9 BDS satellites with PRN numbers 1, 4, 6, 11, 14, 21, 22, 23, and 28, which are connected to a dual-frequency GNSS receiver that can be connected to the network. The dual-frequency GNSS receiver attempts to perform spoofing detection and identification channel by channel.

[0067] The specific implementation steps are as follows: Step 1: Process the received satellite signals through low-noise amplification, down-conversion, analog-to-digital conversion, etc. to obtain digital intermediate-frequency signals.

[0068] Step 2: Capture, track, and demodulate the navigation message for the digital intermediate-frequency signals obtained in Step 1, extract the dual-frequency raw pseudorange observables of each satellite signal, and calculate the satellite elevation angle according to the ephemeris and positioning results. In this example, taking PRN 1 as an example, the satellite elevation angle is , and the dual-frequency pseudoranges are .

[0069] Step 3: Calculate the TEC measurement value and its variance value of each satellite according to Equations (1) and (2). In this example, substituting , the hardware delay difference between the B1 and B3 frequency points of the receiver takes the calibration result , the hardware delay between satellite frequency bands takes the simulated source ephemeris value , the calculated measurement value is , and the measurement uncertainty is .

[0070] Step 4: Obtain the real-time GIM grid information of the day from the International GNSS Service (IGS) website.

[0071] Step 5. According to the approximate receiver position, calculate the ionospheric piercing point longitude and latitude of each satellite to the receiver by a conventional method, and then perform interpolation calculations on the GIM grid and its corresponding root mean square error (RMS) grid in the time dimension and space dimension to obtain the real-time vertical TEC (VTEC) reference value (vertical total electron content reference value) and its uncertainty (vertical uncertainty). In this example, the longitude and latitude given by the receiver are ; the calculated ionospheric piercing point longitude and latitude are , and the reference VTEC value of the ionospheric piercing point interpolated using the GIM grid of the day is (Reference value of total electron content), with an uncertainty of (Target uncertainty).

[0072] Step 6. From and , using Equations (3) and (4), calculate the and in the actual propagation path. In this example, substituting the satellite elevation angle , calculate the equivalent elevation angle , so .

[0073] Step 7. Calculate the detection statistic corresponding to the th satellite according to Equation (5). In this example, substituting the intermediate results calculated in Steps 3 and 5, the detection statistic corresponding to PRN 1 can be calculated as: Step 8. According to the false alarm probability given by the user, calculate the spoofing detection threshold according to Equation (6). Taking as an example, the spoofing detection threshold can be obtained.

[0074] Step 9. Calculate the absolute value of the detection statistic in Step 7, and compare the absolute value of the detection statistic with the spoofing detection threshold in Step 8 to obtain , so the corresponding satellite signal PRN 1 is determined to be a spoofing signal.

[0075] For the remaining 8 satellite signals, repeat the above Steps 3 to 9. The absolute values of the obtained detection statistics all exceed the threshold, indicating that all satellite signals are spoofing signals, that is, all spoofing signals can be detected.

[0076] In the embodiment of the present invention, by using the global ionospheric map grid information obtained by the GNSS user through networking, the real-time or quasi-real-time ionospheric state reference information is further obtained, and compared with the ionospheric state measured by the GNSS user through satellite signals, so as to realize the detection of spoofing signals. Since a large number of current GNSS users (such as smart phones, monitoring stations, intelligent connected vehicles, etc.) can access the Internet and can easily obtain ionospheric reference information, the present invention can be very conveniently implemented at the GNSS user end, and has the advantages of simple implementation, low cost, and good spoofing detection effect. The present invention can significantly improve the spoofing defense ability of GNSS users, and thus ensure the safe and reliable use of the satellite navigation system by users.

[0077] Figure 3This is a schematic diagram of the simulation source experimental scenario provided by the present invention. To verify the effectiveness of the embodiments of the present invention and the technical effects achievable by the embodiments of the present invention, a full-channel dual-frequency spoofing experiment was carried out using the B1I and B3I dual-frequency signals of the Beidou Satellite Navigation System (BDS). The specific test scenario settings are as follows Figure 3 As shown, to simulate the parameter update strategy of a general generation spoofing source, after configuring the simulation source according to the actual Klobuchar ionospheric model parameters on October 17, 2024, it was made to simulate the generation of dual-frequency BDS signals on November 18, so as to simulate the scenario where the spoofing party uses relatively old ionospheric model parameters to simulate the generation of GNSS signals to initiate spoofing interference. The user position simulated by this simulator is 116.33 degrees east longitude, 40 degrees north latitude, and 90 meters in altitude, and the user is in a stationary state.

[0078] After the dual-frequency GNSS receiver receives the satellite signals processed by the RF front end, it first performs baseband signal processing, and then outputs dual-frequency pseudorange observables and satellite elevation angles. At the same time, since the PVT result of the receiver has been completely controlled by the spoofing party, it first obtains the GIM grid information of the day set by the spoofing party from the network, calculates the local VTEC reference value according to the position and time preset by the spoofing party, then uses the SLM model and the elevation angles of each satellite to calculate the TEC reference value of each satellite according to formula (3), and finally subtracts the TEC measurement value from the TEC reference value to calculate the detection statistic of each channel.

[0079] In the experiment, observable data was collected at a rate of 1 Hz for a total of 150 seconds, and the false alarm probability , the frequency-independent pseudorange observation noise variance . The trend of the absolute value of the detection statistic of each satellite channel in the spoofing scenario obtained from the experiment changing with time is shown in Figure 4. Figure 4 This is a schematic diagram showing the change of the absolute value of the detection statistic of each spoofing signal with time under full-channel spoofing provided by the present invention, where different satellites are identified by their pseudo-random code numbers (PRN), and the black dashed line marks the detection threshold.

[0080] The experimental results of the embodiments of the present invention show that the absolute values of the detection statistics of all spoofing signals are higher than the thresholds corresponding to the false alarm probabilities set by the user. Therefore, all spoofing signals can be detected in the experiments of the examples of the embodiments of the present invention.

[0081] Figure 5It is a schematic diagram comparing the absolute value of the difference between the TEC measurement value and the TEC reference value of each signal at a single moment provided by the present invention, and further gives the absolute value of the difference between the TEC measurement value (total electron content measurement value) and the reference value (total electron content reference value) of each PRN in a single moment, that is, the TEC deviation (marked with a red "×"), and the relationship with the corresponding spoofing detection threshold (marked with a black short dash). The results show that the TEC deviations of all spoofing signals exceed the acceptable range of their corresponding detectors, indicating that all spoofing signals broadcast by the simulation source are detected.

[0082] A satellite navigation spoofing detection method, device, equipment and storage medium based on the total electron content deviation provided by the present invention obtain the satellite signals of each satellite, preprocess the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; determine the total electron content measurement value of each satellite based on the dual-frequency raw pseudorange observables; obtain global ionospheric map grid information, and determine the total electron content reference value of each satellite based on the global ionospheric map grid information; determine the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; and judge whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic of each satellite and the spoofing detection threshold. It can accurately detect whether the satellite signal is a spoofing signal and improve the spoofing interference detection ability of the dual-frequency GNSS receiver.

[0083] The satellite navigation spoofing detection device based on the total electron content deviation provided by the present invention will be described below. The satellite navigation spoofing detection device based on the total electron content deviation described below can be mutually referred to the satellite navigation spoofing detection method described above.

[0084] As Figure 6 shown is a schematic structural diagram of a satellite navigation spoofing detection device based on the total electron content deviation provided by the present invention. A satellite navigation spoofing detection device based on the total electron content deviation includes the following modules: A preprocessing module 610, configured to obtain the satellite signals of each satellite, and preprocess the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; A total electron content measurement value determination module 620, configured to determine the total electron content measurement value of each satellite based on the dual-frequency raw pseudorange observables; A total electron content reference value determination module 630, configured to obtain global ionospheric map grid information, and determine the total electron content reference value of each satellite based on the global ionospheric map grid information; A detection statistic determination module 640, configured to determine the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; The deception signal determination module 650 is configured to determine whether the satellite signal of each corresponding satellite is a deception signal based on the detection statistic of each satellite and the deception detection threshold.

[0085] Preferably, the satellite navigation deception detection device based on the total electron content deviation provided by the present invention is specifically configured to perform a first rule process on the satellite signal to obtain a corresponding digital intermediate frequency signal; Perform a second rule process on the digital intermediate frequency signal to obtain a dual-frequency raw pseudorange observation corresponding to the satellite signal; Wherein, the first rule process at least includes low-noise amplification, down-conversion, and analog-to-digital conversion processing, and the second rule process at least includes acquisition, tracking, and message demodulation processing.

[0086] Preferably, the satellite navigation deception detection device based on the total electron content deviation provided by the present invention is specifically configured to calculate the longitude and latitude of the ionospheric piercing point of each satellite to the receiver according to the preset position information of the receiver; Based on the global ionospheric map grid information and the longitude and latitude of the ionospheric piercing point, calculate the real-time vertical total electron content reference value and the corresponding vertical uncertainty of the corresponding piercing point; Based on the real-time vertical total electron content reference value, the vertical uncertainty, and the single-layer spherical shell model, calculate the total electron content reference value and the corresponding target uncertainty on the actual satellite signal propagation path.

[0087] Preferably, the satellite navigation deception detection device based on the total electron content deviation provided by the present invention is specifically configured to calculate a variance value corresponding to the total electron content measurement value while determining the total electron content measurement value of each satellite based on the dual-frequency raw pseudorange observation; The determination of the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value is specifically configured to calculate the detection statistic of each satellite based on the total electron content measurement value, the total electron content reference value, the variance value, and the target uncertainty.

[0088] Preferably, the satellite navigation deception detection device based on the total electron content deviation provided by the present invention is specifically configured to obtain a preset false probability; Calculate the false probability and the inverse function of the Gaussian right tail function to obtain the deception detection threshold.

[0089] Preferably, the satellite navigation deception detection device based on the total electron content deviation provided by the present invention is specifically configured to determine that the satellite signal of the corresponding satellite is a deception signal if the absolute value of the detection statistic of the satellite is greater than the deception detection threshold; If the absolute value of the detection statistic of the satellite is less than or equal to the spoofing detection threshold, it is determined that the satellite signal of the corresponding satellite is a genuine signal.

[0090] A satellite navigation spoofing detection method, device, equipment and storage medium based on the total electron content deviation provided by the present invention obtain the satellite signals of each satellite, preprocess the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; determine the total electron content measurement values of each satellite based on the dual-frequency raw pseudorange observables; obtain global ionospheric map grid information, and determine the total electron content reference values of each satellite based on the global ionospheric map grid information; determine the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; and determine whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic of each satellite and the spoofing detection threshold. It can accurately detect whether the satellite signal is a spoofing signal and improve the spoofing interference detection ability of the dual-frequency GNSS receiver.

[0091] Figure 7 An example of the physical structure diagram of an electronic device is shown as Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740. Among them, the processor 710, the communication interface 720, and the memory 730 communicate with each other through the communication bus 740. The processor 710 can call the logical instructions in the memory 730 to execute a satellite navigation spoofing detection method based on the total electron content deviation. The method includes: obtaining the satellite signals of each satellite, preprocessing the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; determining the total electron content measurement values of each satellite based on the dual-frequency raw pseudorange observables; obtaining global ionospheric map grid information, and determining the total electron content reference values of each satellite based on the global ionospheric map grid information; determining the detection statistic of each satellite based on the total electron content measurement value and the total electron content reference value; and determining whether the satellite signal of each corresponding satellite is a spoofing signal based on the detection statistic of each satellite and the spoofing detection threshold.

[0092] In addition, when the logical instructions in the above-mentioned memory 730 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0093] On the other hand, the present invention also provides a computer program product. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a satellite navigation spoofing detection method based on the total electron content deviation provided by the above-mentioned various methods. The method includes: obtaining the satellite signals of each satellite, and preprocessing the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; based on the dual-frequency raw pseudorange observables, determining the total electron content measurement value of each satellite; obtaining global ionospheric map grid information, and based on the global ionospheric map grid information, determining the total electron content reference value of each satellite; based on the total electron content measurement value and the total electron content reference value, determining the detection statistic of each satellite; based on the detection statistic of each satellite and the spoofing detection threshold, determining whether the satellite signal of each corresponding satellite is a spoofing signal.

[0094] On another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements a satellite navigation spoofing detection method based on the total electron content deviation provided by the above-mentioned various methods. The method includes: obtaining the satellite signals of each satellite, and preprocessing the satellite signals to obtain dual-frequency raw pseudorange observables corresponding to the satellite signals; based on the dual-frequency raw pseudorange observables, determining the total electron content measurement value of each satellite; obtaining global ionospheric map grid information, and based on the global ionospheric map grid information, determining the total electron content reference value of each satellite; based on the total electron content measurement value and the total electron content reference value, determining the detection statistic of each satellite; based on the detection statistic of each satellite and the spoofing detection threshold, determining whether the satellite signal of each corresponding satellite is a spoofing signal.

[0095] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0096] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or equivalently replace some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A satellite navigation spoofing detection method based on total electron number deviation, characterized in that: include: Acquire a satellite signal of each satellite, and preprocess the satellite signal to obtain a dual-frequency original pseudo-range observation corresponding to the satellite signal; Determine a total electron count measurement value of each satellite based on the dual-frequency raw pseudorange observations; Acquire global ionosphere map grid information, and determine a total electron number reference value of each satellite based on the global ionosphere map grid information; Determine a detection statistic of each satellite based on the total electron number measurement value and the total electron number reference value; Based on the detection statistic of each satellite and the spoofing detection threshold, it is determined whether the satellite signal of each corresponding satellite is a spoofing signal.

2. The satellite navigation spoofing detection method based on total electron number deviation according to claim 1 is characterized in that: The preprocessing of the satellite signal to obtain a dual-frequency original pseudo-range observation value corresponding to the satellite signal includes: Performing first rule processing on the satellite signal to obtain a corresponding digital intermediate frequency signal; Performing second rule processing on the digital intermediate frequency signal to obtain a dual-frequency original pseudo-range observation value corresponding to the satellite signal; The first rule processing at least includes low noise amplification, down conversion, and analog-to-digital conversion processing, and the second rule processing at least includes capture, tracking, and message demodulation processing.

3. The satellite navigation spoofing detection method based on total electron number deviation according to claim 1 is characterized in that: Determining a total electron count reference value of each satellite based on the global ionosphere map grid information includes: According to the preset position information of the receiver, the longitude and latitude of the ionospheric puncture point from each satellite to the receiver are calculated; Based on the global ionospheric map grid information and the longitude and latitude of the ionospheric puncture point, a real-time vertical total electron count reference value and a corresponding vertical uncertainty of the corresponding puncture point are calculated; Based on the real-time vertical total electron number reference value, the vertical uncertainty and the single-layer spherical shell model, the total electron number reference value and the corresponding target uncertainty on the actual satellite signal propagation path are calculated.

4. The satellite navigation deception detection method based on total electron number deviation according to claim 3 is characterized in that: While determining the total electron number measurement value of each satellite based on the dual-frequency original pseudorange observation value, calculating the variance value corresponding to the total electron number measurement value; The method of determining the detection statistic of each satellite based on the total electron number measurement value and the total electron number reference value comprises: The detection statistic of each satellite is calculated based on the total electron number measurement value, the total electron number reference value, the variance value and the target uncertainty.

5. The satellite navigation spoofing detection method based on total electron number deviation according to any one of claims 1 to 4, characterized in that: The step of determining the deception detection threshold comprises: Get the preset false probability; The false probability and the inverse function of the Gaussian right tail function are calculated to obtain the deception detection threshold.

6. The satellite navigation spoofing detection method based on total electron number deviation according to any one of claims 1 to 4, characterized in that: The determining, based on the detection statistic of each satellite and the spoofing detection threshold, whether the satellite signal of each corresponding satellite is a spoofing signal comprises: If the absolute value of the detection statistic of the satellite is greater than the spoofing detection threshold, determining that the satellite signal of the corresponding satellite is a spoofing signal; If the absolute value of the detection statistic of a satellite is less than or equal to the spoofing detection threshold, the satellite signal of the corresponding satellite is determined to be a real signal.

7. A satellite navigation deception detection device based on total electronic number deviation, characterized in that: include: A preprocessing module, used to obtain a satellite signal of each satellite and preprocess the satellite signal to obtain a dual-frequency original pseudo-range observation corresponding to the satellite signal; A total electron number measurement value determination module is used to determine the total electron number measurement value of each satellite based on the dual-frequency original pseudorange observation value; A total electron number reference value determination module is used to obtain global ionosphere map grid information and determine the total electron number reference value of each satellite based on the global ionosphere map grid information; A detection statistic determination module is used to determine the detection statistic of each satellite based on the total electron number measurement value and the total electron number reference value; The deception signal determination module is used to determine whether the satellite signal of each corresponding satellite is a deception signal based on the detection statistic of each satellite and the deception detection threshold.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the satellite navigation deception detection method based on total electron number deviation as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the satellite navigation spoofing detection method based on total electron number deviation as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the satellite navigation spoofing detection method based on total electron number deviation as described in any one of claims 1 to 6 is implemented.

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