Real-time deception signal blocking method and system based on satellite power monitoring

Abstract

The present invention discloses a real-time deception signal blocking method and system based on satellite power monitoring, which relates to the field of data security detection technology, including receiving navigation satellite signals, capturing and tracking the signals; preprocessing the signals, separating the background noise and external noise and accurately measuring the background noise power; performing feature analysis on the received signals, distinguishing normal signals from deception signals; and suppressing the deception signals after detecting the deception signals, performing interference response and suspending timing. The method of the present invention uses two-dimensional parallel capture of spread spectrum codes and carrier frequencies, combined with extended Kalman filtering for dynamic signal tracking, to achieve deep integration of signal capture, feature analysis and timing protection, and significantly improve the anti-deception performance of the system in complex environments.

Description

Technical Field

[0001] The present invention relates to the technical field of data security detection, and in particular to a real-time deception signal blocking method and system based on satellite power monitoring. Background Art

[0002] As the core technology of modern positioning, timing and navigation, satellite navigation system plays an irreplaceable role in scientific research. With the widespread application of global navigation satellite system (GNSS), multi-mode systems including Beidou (BDS), GPS, GLONASS and Galileo have been put into operation one after another, and their performance has been continuously optimized and their accuracy has gradually improved. However, the openness and fragility of satellite navigation signals make them vulnerable to interference and spoofing signals, especially in critical applications that require high-precision timing, such as power grid time synchronization, drone control and financial transactions. Traditional anti-interference technologies, such as spectrum filtering and spatial filtering, have achieved certain results in suppressing external noise interference, but these methods are often powerless in the face of advanced spoofing signals (such as analog and forwarding spoofing signals).

[0003] In recent years, deception signal detection methods based on signal feature analysis have gradually attracted attention, including power detection, ephemeris consistency check, Doppler frequency shift analysis and other technical means have been widely studied. For deception detection in dynamic scenes, some improved methods such as the combination of extended Kalman filter (EKF) and pseudorange residual analysis have shown certain potential in the field of navigation and positioning. The continuous development of these technologies provides theoretical support for anti-interference and anti-deception in highly dynamic and complex environments. However, how to strike a balance between real-time and accuracy, and how to effectively combine power, time and frequency characteristics in multi-level signal verification are still urgent problems to be solved by existing technologies. Traditional anti-deception methods often rely on the analysis of a single feature (such as power or time characteristics) in the process of deception signal detection, which leads to misjudgment or missed judgment when the advanced deception signal has strong camouflage. Secondly, for application scenarios with high real-time requirements (such as real-time navigation of drones), the existing algorithms cannot meet the rapid response requirements in dynamic environments due to their high computational complexity. In addition, in multipath signal interference, the existing technology lacks accurate suppression of pseudo-correlation peaks, which often leads to error accumulation and further affects the timing and positioning accuracy. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by the present invention is that the existing satellite navigation technology has the problem that the signal is easily interfered and deceived, and cannot effectively deal with the positioning error and timing deviation caused by advanced deceptive signals.

[0006] To solve the above technical problems, the present invention provides the following technical solutions: a real-time deception signal blocking method based on satellite power monitoring, comprising:

[0007] Receive navigation satellite signals and capture and track the signals;

[0008] Pre-process the signal, separate the background noise from the external noise and accurately measure the background noise power;

[0009] Perform feature analysis on received signals to distinguish normal signals from spoofed signals;

[0010] After the spoofing signal is detected, the spoofing signal is suppressed and the interference response is performed to suspend the timing;

[0011] Furthermore, the feature analysis of the received signal includes distinguishing deceptive signals through graded screening.

[0012] As a preferred solution of the real-time spoof signal blocking method based on satellite power monitoring of the present invention, the receiving of the navigation satellite signal includes: the receiver receives the navigation satellite signal wirelessly from an open space, and receives various external interferences and noises while receiving the satellite signal;

[0013] The signal acquisition and tracking includes detecting the power of the received satellite signal, receiving the power of the satellite transmitted signal within the predicted range, and measuring the distance to the ground; performing two-dimensional parallel search in the time domain and the frequency domain to quickly acquire the pseudo-random noise code and carrier frequency of the signal;

[0014] Normalize the multipath signals, give priority to signal paths with stable power, and reduce interference from pseudo-correlation peaks; dynamically track signals, use the extended Kalman filter algorithm to update the pseudo-range and carrier phase parameters of the signal in real time, track multiple signal channels at the same time, support multi-signal parallel processing, and track real signals and potential deception signals at the same time.

[0015] As a preferred solution of the real-time deception signal blocking method based on satellite power monitoring described in the present invention, wherein: the preprocessing of the signal includes filtering and gain control of the signal, integrating an anti-interference module, including spectrum control and spatial filtering technology, and preliminarily shielding strong interference signals;

[0016] A multi-stage filtering solution is used. The first stage of filtering: at the back end of the antenna, a broadband filter is used to suppress out-of-band interference; the second stage of filtering: at the input end of the receiving module, a narrowband bandpass filter is used to further extract the target frequency band signal;

[0017] Noise floor power measurement, collect the noise floor power during receiver operation , calculate its mean and standard deviation :

[0018] ,

[0019] Noise separation, real-time measurement of total received noise power :

[0020] ,

[0021] Based on baseline noise floor , estimate external noise :

[0022] ,

[0023] in, represents the length of the observation time window, Indicates the receiver at time The background noise signal at each moment; the total noise power is measured in real time, and the background noise model is subtracted to dynamically calculate the external noise power; the external noise is divided into broadband noise, impulse noise and narrowband interference signals using spectrum analysis, and processed separately.

[0024] As a preferred solution of the real-time deception signal blocking method based on satellite power monitoring of the present invention, wherein: the feature analysis of the received signal includes distinguishing the deception signal by graded screening;

[0025] Perform power anomaly analysis and define the first-level screening: using the real-time collected signal power , perform anomaly detection of basic features and quickly eliminate obvious abnormal signals;

[0026] The real-time collected signal power values ​​are formed into a power time series to analyze the power changes in a short period of time; if the power increases or decreases abnormally in a short period of time, it is initially marked as a power abnormality signal; the power volatility of the detection signal is detected. If the power fluctuation is severe and exceeds the historical statistical fluctuation range of the normal signal, it is marked as a fluctuation abnormality signal;

[0027] Definition of the judgment index includes: power variation range , short-term volatility , power threshold and fluctuation threshold , allowable fluctuation range ;

[0028] like , marked as a preliminary anomaly; if , marked as fluctuation anomaly; output the marked result as input for subsequent verification.

[0029] As a preferred solution of the real-time spoofing signal blocking method based on satellite power monitoring described in the present invention, the distinction between normal signals and spoofing signals includes secondary verification, power distance consistency verification, and for signals marked as abnormal in the primary screening, using satellite orbit information and receiving device position to calculate the theoretical power. And compared with the actual power, Indicates the power change threshold;

[0030] The power deviation formula is expressed as:

[0031] ,

[0032] like , then the signal is normal and returns to the first level; like , enter the third level verification; use the second level verification results to update the first level power threshold and fluctuation threshold , dynamically optimize the initial screening rules;

[0033] For suspected abnormal signals that have passed the second-level verification, consistency detection is performed through data from multiple receiving points, which is defined as three-time verification; power distribution consistency index , calculate the multi-point power consistency, the formula is expressed as:

[0034] ,

[0035] like , marked as an abnormal signal, and enter the fourth level analysis; if , return to the secondary optimization threshold and re-verify other signals;

[0036] For signals marked as abnormal in the third-level verification, advanced verification is performed by combining time series and spectrum analysis, which is defined as the fourth-level verification;

[0037] Time rate of change , the frequency distribution deviation is expressed as ; Check the power time rate of change :

[0038] ,

[0039] If it exceeds the range, it is marked as a dynamic abnormal signal; check the power spectrum deviation, the formula is expressed as:

[0040] ,

[0041] like , judged as a spectrum abnormal signal; combined with the time and frequency results, make a final judgment. If the signal is abnormal in both time and frequency, it is judged as a deception signal. If only one aspect is abnormal, return to level three and re-verify the consistency;

[0042] It supports spoofing signal recognition, performs two-dimensional parallel capture of spread spectrum codes in the frequency domain and time domain during the signal acquisition phase, and uses multiple tracking channels to simultaneously track real satellite signals and spoofing signals during the signal tracking phase.

[0043] As a preferred solution of the real-time spoofing signal blocking method based on satellite power monitoring described in the present invention, the spoofing signal suppression includes: using the pseudo-range residuals of each satellite to detect whether there is a spoofing signal during the solution process, and after completing the solution to obtain the position and time information, using the position deviation information to detect whether the positioning result is reasonable and whether there is a spoofing signal;

[0044] In the case of suspected spoofing signals, the timing service is suspended to ensure that the output time information is credible; the satellite signal marked as suspected spoofing signal is suspended from using its data for timing calculation;

[0045] During the timing process, only signals with normal pseudorange residuals and position deviations are retained to participate in the time information output to ensure the credibility of the timing results. If a deceptive signal is found, the timing is suspended. The deceptive signal is not directly eliminated to ensure the output of credible time information.

[0046] As a preferred solution of the real-time deception signal blocking method based on satellite power monitoring described in the present invention, the interference response suspension timing includes making a comprehensive decision based on the results at all levels:

[0047] When a single-level abnormality occurs during multi-level verification, it is judged as a noise misjudgment and marked as temporarily normal;

[0048] Level 1 and 2 are abnormal but level 3 and 4 are normal; level 1 and 2 are normal but level 3 and 4 are abnormal: It is judged as a potential deception signal, and a warning is issued first, and multiple tracking channels are tracked simultaneously;

[0049] When abnormal signals appear at three or four levels in multi-level verification, they are directly marked as fraudulent signals, triggering the blocking mechanism.

[0050] As a preferred solution of the real-time deception signal blocking system based on satellite power monitoring described in the present invention, wherein:

[0051] The signal receiving module is responsible for receiving navigation satellite signals, processing background noise and external interference, and realizing signal preprocessing, including noise separation and preliminary filtering;

[0052] Signal acquisition module, satellite signal acquisition, tracking and multi-path processing. Supports multi-channel tracking of real signals and deceptive signals;

[0053] Signal feature analysis and discrimination module, which screens and discriminates signal features in a graded manner, distinguishing normal signals from deceptive signals;

[0054] The anti-interference module suppresses deceptive signals and suspends timing to ensure that the output results are credible.

[0055] A computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement a step of a real-time spoof signal blocking method based on satellite power monitoring.

[0056] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of a real-time spoof signal blocking method based on satellite power monitoring.

[0057] Beneficial effects of the invention: The real-time deception signal blocking method based on satellite power monitoring provided by the invention adopts two-dimensional parallel capture of spread spectrum codes and carrier frequencies, combined with extended Kalman filtering for dynamic signal tracking, to achieve deep integration of signal capture, feature analysis and timing protection, and significantly improve the system's anti-deception performance in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0059] Figure 1 An overall flow chart of a real-time spoofing signal blocking method based on satellite power monitoring provided in the first embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0061] Example 1, reference Figure 1 , is an embodiment of the present invention, and provides a real-time spoofing signal blocking method based on satellite power monitoring, comprising:

[0062] S1: Receive navigation satellite signals and capture and track the signals.

[0063] Furthermore, the receiving of navigation satellite signals includes the receiver receiving the navigation satellite signals wirelessly from an open space, and receiving various external interferences and noises while receiving the satellite signals.

[0064] Furthermore, the signal capture and tracking includes detecting the power of the received satellite signal, receiving the satellite transmitted signal power within a predicted range and measuring the distance to the ground; performing two-dimensional parallel search in the time domain and frequency domain to quickly capture the signal's pseudo-random noise code and carrier frequency.

[0065] Furthermore, the satellite transmits signal power Obtained through the navigation signal interface specification. After the signal reaches the ground, the power prediction formula is:

[0066] ,

[0067] in:

[0068] ,

[0069] in, Indicates the distance from the satellite to the ground (unit: km); Indicates the signal frequency (unit: MHz).

[0070] Furthermore, the signal power measurement uses the signal power detection module to measure the received signal power. . With the predicted power Compare and determine whether the signal is within a reasonable range. Calculate the satellite position based on the navigation message using the pseudo-range formula.

[0071] Furthermore, the multipath signals are normalized, and the signal paths with stable power are given priority to reduce the interference of pseudo-correlation peaks. Dynamic signal tracking uses the extended Kalman filter algorithm to update the pseudo-range and carrier phase parameters of the signal in real time, and track multiple signal channels at the same time, supporting multi-signal parallel processing and tracking real signals and potential deception signals at the same time.

[0072] It should be noted that the signal quality assessment is performed: the signal quality is assessed based on parameters such as signal-to-noise ratio (C / N0) and pseudorange residual. A high-quality signal path is selected as the main path for timing. The dynamic changes of each signal path are recorded. If a path parameter (such as pseudorange rate) deviates from the normal range, it is marked as a suspected spoofing signal.

[0073] S2: Preprocess the signal, separate the background noise and external noise, and accurately measure the background noise power.

[0074] Furthermore, the preprocessing of the signal includes filtering and gain control of the signal, integrating an anti-interference module, including spectrum control and spatial filtering technology, to preliminarily shield strong interference signals.

[0075] A multi-stage filtering solution is used. The first stage of filtering is at the back end of the antenna, where a broadband filter is used to suppress out-of-band interference. The second stage of filtering is at the input end of the receiving module, where a narrowband bandpass filter is used to further extract the target frequency band signal.

[0076] First-stage filtering: A broadband filter is used at the back end of the antenna. It suppresses out-of-band signals and prevents them from entering the receiving module, protecting the front-end low noise amplifier (LNA) from strong interference signals. A broadband bandpass filter is used with a center frequency of Corresponding to the target satellite signal frequency band, the bandwidth is wider than the target signal frequency range. The filtered signal is:

[0077] ,

[0078] in, is the frequency response of the broadband filter.

[0079] Secondary filtering: A narrowband bandpass filter is used at the input of the receiving module. Goal: Further extract the target frequency band signal and eliminate out-of-band interference that is not completely shielded by the primary filtering. Implementation: The narrowband bandpass filter has higher selectivity and the center frequency Accurately locate the satellite signal frequency, and the bandwidth strictly matches the signal frequency range. The filtered signal is:

[0080] ,

[0081] in is the frequency response of the narrowband filter.

[0082] Total noise power measurement, receive signal input ,in, For signal, For noise.

[0083] After passing through the bandpass filter, the total signal of the target frequency band is extracted, including noise and signal. The formula for calculating the total power is expressed as:

[0084] ,

[0085] in, Indicates the sampling time window (such as 1 ms or 10 ms). Indicates the instantaneous amplitude of the input signal.

[0086] Noise power statistics, record long-term noise power when the signal is weak or shielded The mean of the statistical noise and standard deviation

[0087] ,

[0088] in, Indicates the number of samples in the sampling window.

[0089] Noise floor power measurement, collect the noise floor power during receiver operation , calculate its mean and standard deviation :

[0090] ,

[0091] Noise separation, real-time measurement of total received noise power :

[0092] ,

[0093] Based on the baseline noise floor , estimate external noise :

[0094] ,

[0095] in, represents the length of the observation time window, Indicates the receiver at time The background noise signal at each moment; the total noise power is measured in real time, and the background noise model is subtracted to dynamically calculate the external noise power; the external noise is divided into broadband noise, impulse noise and narrowband interference signals using spectrum analysis, and processed separately.

[0096] It should be noted that broadband noise: It is flatly distributed within the frequency spectrum and is processed by adaptive filtering. Impulse noise: There are high-frequency spikes in the frequency domain and the processing method is transient noise suppression in the time domain. Narrowband interference: There are narrowband high-energy peaks in the spectrum and the processing method is band-stop filtering.

[0097] S3: Perform feature analysis on the received signal to distinguish normal signals from spoofed signals.

[0098] Furthermore, the feature analysis of the received signal includes distinguishing deceptive signals through graded screening;

[0099] Perform power anomaly analysis and define the first-level screening: using the real-time collected signal power , perform anomaly detection of basic features and quickly eliminate obvious abnormal signals.

[0100] The signal power values ​​collected in real time are formed into a power time series to analyze the changes in power in a short period of time. If the power increases or decreases abnormally in a short period of time, it is initially marked as a power abnormality signal. The power volatility of the detection signal is detected. If the power fluctuation is severe and exceeds the historical statistical fluctuation range of the normal signal, it is marked as a fluctuation abnormality signal.

[0101] Definition of the judgment index includes: power variation range , short-term volatility , power threshold and fluctuation threshold , allowable fluctuation range .

[0102] like , marked as a preliminary anomaly; if , marked as fluctuation anomaly; output the marked result as input for subsequent verification.

[0103] The method of distinguishing normal signals from spoofed signals includes the second level verification, power distance consistency verification, and for signals marked as abnormal in the first level screening, calculating the theoretical power using satellite orbit information and the location of the receiving device. And compare with the actual power.

[0104] The power deviation formula is expressed as:

[0105] ,

[0106] like , then the signal is normal and returns to level one; if , enter the third level verification; use the second level verification results to update the first level power threshold and fluctuation threshold , dynamically optimize the initial screening rules.

[0107] For suspected abnormal signals that have passed the second-level verification, consistency detection is performed through data from multiple receiving points, which is defined as three-time verification; power distribution consistency index , calculate the multi-point power consistency, the formula is expressed as:

[0108] ,

[0109] like , marked as an abnormal signal, and enter the fourth level analysis; if , return to the secondary optimization threshold and re-verify other signals.

[0110] For the signals marked as abnormal in the third-level verification, advanced verification is performed by combining time series and spectrum analysis, which is defined as the fourth-level verification.

[0111] Time rate of change , the frequency distribution deviation is expressed as ; Check the power time rate of change :

[0112] ,

[0113] If it exceeds the range, it is marked as a dynamic abnormal signal; check the power spectrum deviation, the formula is expressed as:

[0114] ,

[0115] like , it is determined to be a spectrum abnormal signal; combined with the time and frequency results, a final judgment is made. If the signal is abnormal in both time and frequency, it is determined to be a deception signal. If only one aspect is abnormal, it returns to level three and re-verifies the consistency.

[0116] It should be noted that it supports spoofing signal recognition, performs two-dimensional parallel capture of spread spectrum codes in the frequency domain and time domain in the signal capture phase, and uses multiple tracking channels to simultaneously track real satellite signals and spoofing signals in the signal tracking phase.

[0117] S4: After the spoofing signal is detected, the spoofing signal is suppressed and the interference response is performed to suspend the timing.

[0118] Furthermore, the spoofing signal suppression includes, during the solution process, using the pseudo-range residuals of each satellite to detect whether there is a spoofing signal, and after completing the solution to obtain the position and time information, using the position deviation information to detect whether the positioning result is reasonable and whether there is a spoofing signal.

[0119] In the case of suspected spoofing signals, suspend timing to ensure that the output time information is credible; suspend the use of data from satellite signals marked as suspected spoofing signals for timing calculations.

[0120] During the timing process, only signals with normal pseudorange residuals and position deviations are retained to participate in the time information output to ensure the credibility of the timing results. If a deceptive signal is found, the timing is suspended. The deceptive signal is not directly eliminated to ensure the output of credible time information.

[0121] The interference response suspension timing includes making a comprehensive decision based on the results at all levels.

[0122] When a single-level abnormality occurs during multi-level verification, it is judged as a noise misjudgment and marked as temporarily normal.

[0123] Level 1 and 2 are abnormal but level 3 and 4 are normal; level 1 and 2 are normal but level 3 and 4 are abnormal: They are judged as potential deception signals, and warnings are issued first, and multiple tracking channels are tracked simultaneously.

[0124] When abnormal signals appear at three or four levels in multi-level verification, they are directly marked as fraudulent signals, triggering the blocking mechanism.

[0125] Example 2: The following is an embodiment of the present invention, which provides a real-time deception signal blocking method based on satellite power monitoring. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0126] In order to verify the effectiveness of the real-time deception signal blocking method based on satellite power monitoring, this experiment designed a complete test process of navigation signal reception, processing and deception signal detection. The experiment built a complex test scenario including multi-path signals, multi-noise interference and pseudo signal injection to verify the signal capture and tracking, noise separation, feature analysis and deception signal blocking process, and compared it with the existing technology.

[0127] Test preparation:

[0128] Navigation signal receiver, with broadband and narrowband filtering functions. Signal injector, used to simulate real signals and pseudo signals. Signal analyzer, supporting spectrum analysis and signal feature extraction. Pseudo signal injection module, used to simulate deceptive signals of different power and characteristics.

[0129] Signal scenario design: Real navigation signal: 4 Beidou satellite signals, pseudo-range noise of 3m, power range of -125dBm to -130dBm. Interference signal: broadband noise, narrowband interference and pulse noise, power range of -110dBm to -90dBm. Spoofing signal: simulated pseudo signal, power set to -100dBm to -115dBm, injected into the receiving path at different locations.

[0130] Implementation process:

[0131] Signal capture and tracking: The receiver performs a two-dimensional search on the signal received by the antenna, capturing the pseudo-random noise code (PRN) in the time domain and the carrier frequency in the frequency domain. The extended Kalman filter is used to update the pseudo-range and carrier phase parameters in real time, and the multiple signal paths are normalized, giving priority to the power stable path.

[0132] Signal preprocessing: First-stage filtering: The broadband filter initially suppresses out-of-band interference, and the signal frequency band range is set to 1555MHz to 1577 MHz. Second-stage filtering: The narrowband filter further extracts the target frequency band signal, with a bandwidth of 2 MHz and a center frequency set to 1575.42 MHz. Background noise measurement and separation: The background noise model is established through long-term acquisition, the total noise power is calculated in real time, and the baseline noise is deducted, and the external noise is dynamically separated.

[0133] Signature Analysis and Deception Signal Detection:

[0134] Level 1 screening: Detect power anomalies and fluctuations, define power thresholds (-120dBm) and fluctuation thresholds (±3dBm), and screen preliminary abnormal signals. Level 2 verification: Compare actual power with theoretical power. If the power deviation exceeds ±5dBm, mark it as a suspected abnormal signal. Level 3 verification: Multi-receiving point data consistency detection. When the power distribution consistency index is lower than 0.85, it is marked as abnormal. Level 4 verification: Through time series and spectrum analysis, if the signal has both dynamic and spectrum abnormal characteristics, it is judged as a spoofing signal. For the receiving path marked as a spoofing signal, suspend its data timing participation and only retain normal signals for time output. Ensure that the time information output by the timing system is credible.

[0135] Table 1 Simulation data record table

[0136] ,

[0137] It can be seen from the table data that in this embodiment, through signal capture, tracking, feature analysis and separation processing, deception signals and strong interference signals can be effectively detected, and they can be accurately shielded and marked. The power fluctuation of the real signal is kept within ±2dBm, the power deviation is less than 0.5dBm, the pseudo-range noise is less than 3m, and the spectrum deviation is 0, indicating that the receiving path accurately captures and tracks the real satellite signal. The power of the deception signal is significantly higher than the real signal (the deviation exceeds 15dBm), the power fluctuation greatly exceeds the threshold, and the spectrum deviation reaches more than 150Hz. After multi-level verification, the signal was accurately marked as abnormal, successfully avoiding system misjudgment.

[0138] Broadband noise, narrowband interference and pulse interference signals were all detected as interference sources, and their characteristics, such as power fluctuation (up to 20dBm) and spectrum deviation (300Hz), were obviously abnormal, verifying the effective suppression capability of the multi-stage filtering scheme on interference signals.

[0139] Embodiment 3, the following is an embodiment of the present invention, which provides a real-time spoofing signal blocking system based on satellite power monitoring, including:

[0140] The signal receiving module is responsible for receiving navigation satellite signals, processing background noise and external interference, and realizing signal preprocessing, including noise separation and preliminary filtering.

[0141] Signal acquisition module, satellite signal acquisition, tracking and multi-path processing. Supports multi-channel tracking of real signals and spoofed signals.

[0142] The signal feature analysis and discrimination module screens and discriminates signal features in a graded manner, distinguishing normal signals from deceptive signals.

[0143] The anti-interference module suppresses deceptive signals and suspends timing to ensure that the output results are credible.

[0144] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0145] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0146] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk case (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0147] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logical function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0148] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A real-time deception signal blocking method based on satellite power monitoring, characterized in that: include: Receive navigation satellite signals and capture and track the signals; Pre-process the signal, separate the background noise from the external noise and accurately measure the background noise power; Perform feature analysis on received signals to distinguish normal signals from spoofed signals; After the spoofing signal is detected, the spoofing signal is suppressed and the interference response is performed to suspend the timing; Furthermore, the feature analysis of the received signal includes distinguishing deceptive signals through graded screening; The characteristic analysis of the received signal includes distinguishing deceptive signals through graded screening; Perform power anomaly analysis and define the first-level screening: Use the real-time collected signal power P(t) to perform anomaly detection of basic features and quickly eliminate obvious abnormal signals; The real-time collected signal power values ​​are formed into a power time series to analyze the power changes in a short period of time; if the power increases or decreases abnormally in a short period of time, it is initially marked as a power abnormality signal; the power volatility of the detection signal is detected. If the power fluctuation is severe and exceeds the historical statistical fluctuation range of the normal signal, it is marked as a fluctuation abnormality signal; The defined judgment indicators include power variation amplitude ΔP, short-term volatility σ P , power threshold ΔP threshold and fluctuation threshold Allowable fluctuation range δ; If |ΔP|>ΔP threshold , marked as a preliminary anomaly; if Mark as abnormal fluctuation; output the marking result as input for subsequent verification; The method of distinguishing normal signals from spoofed signals includes the second level verification, power distance consistency verification, and for signals marked as abnormal in the first level screening, calculating the theoretical power P using satellite orbit information and the location of the receiving device. theoretical And compared with the actual power, ΔP distance,threshold Indicates the power change threshold; The power deviation formula is expressed as: ΔP distance =|P(t)-P theoretical | If ΔP distance ≤ΔP distance,threshold , the signal is normal and returns to level one; if ΔP distance >ΔP distance,threshold , enter the third level verification; use the second level verification result to update the first level power threshold ΔP threshold and fluctuation threshold Dynamically optimize the initial screening rules; For suspected abnormal signals that have passed the secondary verification, consistency detection is performed through data from multiple receiving points, which is defined as three verifications; the power distribution consistency index C P , calculate the multi-point power consistency, the formula is expressed as: like Marked as abnormal signal, enter the fourth level analysis, where P i (t) represents the signal power at time i, Represents the average power of multiple receiving points, represents the consistency threshold; if Return to the secondary optimization threshold and re-verify other signals; For signals marked as abnormal in the third-level verification, advanced verification is performed by combining time series and spectrum analysis, which is defined as the fourth-level verification; The time rate of change ΔP / Δt, the frequency distribution deviation is expressed as S(f)-S baseline (f); Check the power time change rate ΔP / Δt and the power change rate threshold Relationship: If it exceeds the range, it is marked as a dynamic abnormal signal; check the power spectrum deviation, the formula is expressed as: ΔS=∫|S(f)-S baseline (f)|df Among them, ΔS threshold Indicates the power spectrum deviation threshold. If ΔS>ΔS threshold , judged as a spectrum abnormal signal; combined with the time and frequency results, make a final judgment. If the signal is abnormal in both time and frequency, it is judged as a deception signal. If only one aspect is abnormal, return to the third-level verification and re-verify the consistency; It supports spoofing signal recognition, performs two-dimensional parallel capture of spread spectrum codes in the frequency domain and time domain during the signal acquisition phase, and uses multiple tracking channels to simultaneously track real satellite signals and spoofing signals during the signal tracking phase.

2. The real-time spoofing signal blocking method based on satellite power monitoring as claimed in claim 1, characterized in that: The receiving of the navigation satellite signal comprises: the receiver wirelessly receives the navigation satellite signal from an open space, and simultaneously receives various external interferences and noises while receiving the satellite signal; The signal acquisition and tracking includes detecting the power of the received satellite signal, receiving the power of the satellite transmitted signal within the predicted range, and measuring the distance to the ground; Perform two-dimensional parallel search in the time domain and frequency domain to quickly capture the signal's pseudo-random noise code and carrier frequency; Normalize the multipath signals, give priority to signal paths with stable power, and reduce interference from pseudo-correlation peaks; dynamically track signals, use the extended Kalman filter algorithm to update the pseudo-range and carrier phase parameters of the signal in real time, track multiple signal channels at the same time, support multi-signal parallel processing, and track real signals and potential deception signals at the same time.

3. The real-time deception signal blocking method based on satellite power monitoring as claimed in claim 2, characterized in that: The preprocessing of the signal includes filtering and gain control of the signal, integrating an anti-interference module, including spectrum control and spatial filtering technology, and preliminarily shielding strong interference signals; A multi-stage filtering solution is used. The first stage of filtering: at the back end of the antenna, a broadband filter is used to suppress out-of-band interference; the second stage of filtering: at the input end of the receiving module, a narrowband bandpass filter is used to further extract the target frequency band signal; Noise floor power measurement, collect the noise floor power P during receiver operation n,int , calculate its mean μ n,int and standard deviation σ n,int : Noise separation, real-time measurement of the total noise power P received n,total : P n,total =P n,int +P n,ext According to the baseline noise floor P n,int , calculate the external noise P n,ext : P n,ext =P n,total -P n,int Where T represents the length of the observation time window, n init (t) represents the background noise signal of the receiver at time t; the total noise power is measured in real time, and the background noise model is subtracted to dynamically calculate the external noise power; the external noise is divided into broadband noise, pulse noise and narrowband interference signals using spectrum analysis, and processed separately.

4. The real-time deception signal blocking method based on satellite power monitoring as claimed in claim 3 is characterized in that: The spoofing signal suppression includes using the pseudo-range residuals of each satellite to detect whether there is a spoofing signal during the solution process, and after completing the solution to obtain the position and time information, using the position deviation information to detect whether the positioning result is reasonable and whether there is a spoofing signal; In the case of suspected spoofing signals, the timing service is suspended to ensure that the output time information is credible; the satellite signal marked as suspected spoofing signal is suspended from using its data for timing calculation; During the timing process, only signals with normal pseudorange residuals and position deviations are retained to participate in the time information output to ensure the credibility of the timing results. If a deceptive signal is found, the timing is suspended. The deceptive signal is not directly eliminated to ensure the output of credible time information.

5. The real-time deception signal blocking method based on satellite power monitoring as claimed in claim 4, characterized in that: The interference response suspension timing includes making a comprehensive decision based on the results of each level: When a single-level abnormality occurs during multi-level verification, it is judged as a noise misjudgment and marked as temporarily normal; Level 1 and 2 are abnormal but level 3 and 4 are normal; level 1 and 2 are normal but level 3 and 4 are abnormal: It is judged as a potential deception signal, and a warning is issued first, and multiple tracking channels are tracked simultaneously; When abnormal signals appear at three or four levels in multi-level verification, they are directly marked as fraudulent signals, triggering the blocking mechanism.

6. A system using the real-time deception signal blocking method based on satellite power monitoring as claimed in any one of claims 1 to 5, characterized in that: The signal receiving module is responsible for receiving navigation satellite signals, processing background noise and external interference, and realizing signal preprocessing, including noise separation and preliminary filtering; Signal acquisition module, satellite signal acquisition, tracking and multi-path processing, supporting multi-channel tracking of real and deceptive signals; Signal feature analysis and discrimination module, which screens and discriminates signal features in a graded manner, distinguishing normal signals from deceptive signals; The characteristic analysis of the received signal includes distinguishing deceptive signals through graded screening; Perform power anomaly analysis and define the first-level screening: Use the real-time collected signal power P(t) to perform anomaly detection of basic features and quickly eliminate obvious abnormal signals; The real-time collected signal power values ​​are formed into a power time series to analyze the power changes in a short period of time; if the power increases or decreases abnormally in a short period of time, it is initially marked as a power abnormality signal; the power volatility of the detection signal is detected. If the power fluctuation is severe and exceeds the historical statistical fluctuation range of the normal signal, it is marked as a fluctuation abnormality signal; The defined judgment indicators include power variation amplitude ΔP, short-term volatility σ P , power threshold ΔP treshold and fluctuation threshold Allowable fluctuation range δ; If |ΔP|>ΔP threshold , marked as a preliminary anomaly; if Mark as abnormal fluctuation; output the marking result as input for subsequent verification; The method of distinguishing normal signals from spoofed signals includes the second level verification, power distance consistency verification, and for signals marked as abnormal in the first level screening, calculating the theoretical power P using satellite orbit information and the location of the receiving device. theoretical And compared with the actual power, ΔP distance,threshold Indicates the power change threshold; The power deviation formula is expressed as: ΔP distance =|P(t)-P theoretical | If ΔP distance ≤ΔP distance,threshold , the signal is normal and returns to level one; if ΔP distance >ΔP distance,threshold , enter the third level verification; use the second level verification result to update the first level power threshold ΔP threshold and fluctuation threshold Dynamically optimize the initial screening rules; For suspected abnormal signals that have passed the secondary verification, consistency detection is performed through data from multiple receiving points, which is defined as three verifications; the power distribution consistency index C P , calculate the multi-point power consistency, the formula is expressed as: like Marked as abnormal signal, enter the fourth level analysis, where P i (t) represents the signal power at time i, Represents the average power of multiple receiving points, represents the consistency threshold; if Return to the secondary optimization threshold and re-verify other signals; For signals marked as abnormal in the third-level verification, advanced verification is performed by combining time series and spectrum analysis, which is defined as the fourth-level verification; The time rate of change ΔP / Δt, the frequency distribution deviation is expressed as S(f)-S baseline (f); Check the power time change rate ΔP / Δt and the power change rate threshold Relationship: If it exceeds the range, it is marked as a dynamic abnormal signal; check the power spectrum deviation, the formula is expressed as: ΔS=∫|S(f)-S baseline (f)|df Among them, ΔS threshold Indicates the power spectrum deviation threshold. If ΔS>ΔS threshold , judged as a spectrum abnormal signal; combined with the time and frequency results, make a final judgment. If the signal is abnormal in both time and frequency, it is judged as a deception signal. If only one aspect is abnormal, return to the third-level verification and re-verify the consistency; Supports spoofing signal recognition, performs two-dimensional parallel capture of spread spectrum codes in the frequency domain and time domain during the signal acquisition phase, and uses multiple tracking channels to simultaneously track real satellite signals and spoofing signals during the signal tracking phase; The anti-interference module suppresses deceptive signals and suspends timing to ensure that the output results are credible.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the real-time spoof signal blocking method based on satellite power monitoring described in any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the real-time spoof signal blocking method based on satellite power monitoring according to any one of claims 1 to 5 are implemented.

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