A Dual-Antenna Carrier Phase Anti-Spoofing Detection Method Based on DBSCAN Clustering Algorithm
By using the DBSCAN clustering algorithm to detect spoofing signals in GNSS receivers, the problem of poor detection efficiency and applicability in vehicle-mounted application scenarios is solved, and efficient spoofing signal identification and removal without the need for baseline vector information is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- HUNAN BEIYUN TECH CO LTD
- Filing Date
- 2023-08-17
- Publication Date
- 2026-05-26
AI Technical Summary
Existing technologies cannot effectively detect spoofing signals in vehicle-mounted GNSS receivers, especially in dynamic vehicle-mounted application scenarios. Traditional methods require prior knowledge of the antenna baseline vector information, and the inertial navigation system has poor accuracy before initial alignment, making it impossible to accurately estimate the baseline vector.
The DBSCAN clustering algorithm is used to calculate the carrier phase single-difference residual by calibrating the hardware channel and RF cable delay, and to accumulate it over multiple epochs. The DBSCAN clustering algorithm is then used to identify satellites with clustered residuals and to detect spoofing signals.
It can effectively detect spoofing signals without acquiring baseline vector information, improving detection efficiency and adaptability, and enabling rapid identification and removal of affected satellites.
Smart Images
Figure CN117075150B_ABST
Abstract
Description
Technical Field
[0001] This disclosure relates to the field of data processing technology, and in particular to a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm. Background Technology
[0002] GNSS receivers are used in the automotive field to provide vehicles with high-precision position information. However, due to the inherent characteristics of civilian GNSS signals, including their exposed signal interfaces and relatively weak signal strength, genuine signals are easily interfered with by spoofing signals. This can lead to GNSS receivers being misled into obtaining incorrect position results, which can easily cause accidents or other unexpected consequences in the automotive field. Traditional dual / multi-antenna anti-spoofing methods usually require prior knowledge of the antenna baseline vectors. Some methods calculate this using stationary antennas with known positions, but these methods cannot meet the needs of dynamic automotive applications. Some methods rely on inertial navigation systems (INS) to obtain vehicle attitude and baseline length information, and then calculate the real-time dynamic baseline vector. However, in practical applications, the accuracy of INS is poor before initial alignment is completed, and it cannot accurately estimate the baseline vector. In such cases, the method of calculating the baseline using INS is ineffective.
[0003] It is evident that there is an urgent need for an anti-spoofing detection method that can effectively detect spoofing signals without acquiring antenna baseline vector information. Summary of the Invention
[0004] In view of this, the present disclosure provides a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm, which at least partially solves the problems of poor detection efficiency and applicability in the prior art.
[0005] This disclosure provides a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm, including:
[0006] Step 1: Calibrate the hardware channel delay of the two RF front-ends of the receiver connected to the antenna, and calibrate the delay of the two RF cables connected to the antenna.
[0007] Step 2: Calculate the carrier phase single-difference measurement value for each satellite;
[0008] Step 3: Subtract the hardware channel delay, RF cable delay, and integer part from the carrier phase single difference measurement value to obtain the carrier phase single difference residual;
[0009] Step 4: Accumulate the single-difference carrier phase residual over multiple epochs to obtain the multi-epoch accumulated average residual;
[0010] Step 5: Based on the statistical characteristics of the multi-epoch cumulative average residuals, the DBSCAN clustering algorithm is used to identify satellites with clustered residuals.
[0011] Step 6: Perform a threshold test on the number of clustered satellites. Signals with a number of clustered satellites greater than the threshold are marked as deceptive signals, and the clustered satellites are marked as deceptive satellites.
[0012] According to a specific implementation of an embodiment of this disclosure, step 3 specifically includes:
[0013] When there is no deceptive interference signal, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: in, This represents the single-difference ambiguity, with values of integers, bcos(α). i α represents the projection length of the baseline vector onto the line-of-sight vector. i ε represents the angle between the actual signal satellite line-of-sight vector and the baseline vector. real This represents the measurement error of the actual signal;
[0014] When spoofing interference signals are present, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: Where, α spoof ε represents the angle between the deception signal satellite line-of-sight vector and the baseline vector. spoof This indicates a measurement error in the deceptive signal.
[0015] According to a specific implementation of this disclosure, the formula for calculating the carrier phase single-difference residual is as follows: in, The value represents the carrier phase single-difference measurement, i represents the satellite number, u represents the main antenna, r represents the slave antenna, and Δt represents the hardware channel delay and RF cable delay.
[0016] According to a specific implementation of this disclosure, the expression for the multi-epoch cumulative average residual is: Where n is the epochal cumulative number.
[0017] The dual-antenna carrier phase anti-spoofing detection scheme based on the DBSCAN clustering algorithm in this embodiment includes: Step 1, calibrating the hardware channel delay of the two RF front-ends of the receiver connected to the antenna, and calibrating the delay of the two RF cables connected to the antenna; Step 2, calculating the carrier phase single-difference measurement value for each satellite; Step 3, subtracting the hardware channel delay, RF cable delay, and integer part from the carrier phase single-difference measurement value to obtain the carrier phase single-difference residual; Step 4, accumulating the carrier phase single-difference residual over multiple epochs to obtain the multi-epoch accumulated average residual; Step 5, using the DBSCAN clustering algorithm to identify satellites with clustered residuals based on the statistical characteristics of the multi-epoch accumulated average residual; Step 6, performing a threshold test on the number of clustered satellites, marking signals with a clustered satellite number greater than a threshold as spoofing signals, and marking the clustered satellites as spoofing satellites.
[0018] The beneficial effects of the embodiments of this disclosure are as follows: Based on the inherent characteristic that the single-difference carrier phase measurement values between different satellites are similar when the dual antennas receive spoofing signals, the DBSCAN clustering method is used to identify this characteristic, which can effectively detect spoofing signals and remove affected satellites. Spoofing detection can be performed without obtaining the baseline vector information of the dual antennas, thus improving detection efficiency and adaptability. Attached Figure Description
[0019] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0020] Figure 1 This is a flowchart illustrating a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm provided in an embodiment of this disclosure. Detailed Implementation
[0021] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings.
[0022] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. This disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this disclosure. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.
[0023] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this disclosure, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.
[0024] Furthermore, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.
[0025] This disclosure provides a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm, which can be applied to the satellite signal analysis process in vehicle positioning scenarios.
[0026] See Figure 1 This is a flowchart illustrating a dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm provided in an embodiment of this disclosure. Figure 1 As shown, the method mainly includes the following steps:
[0027] Step 1: Calibrate the hardware channel delay of the two RF front-ends of the receiver connected to the antenna, and calibrate the delay of the two RF cables connected to the antenna.
[0028] In practice, the hardware channel delay of the two RF front-ends used to connect the antennas of the receiver can be calibrated in advance, and the antennas can be connected using RF cables of equal length or the delay of the two RF cables connecting the antennas can be calibrated during the application process.
[0029] Step 2: Calculate the carrier phase single-difference measurement value for each satellite;
[0030] In practice, the carrier phase difference measurement values of the two antennas can be calculated using a measuring device connected to each antenna port. Where i represents the satellite number, u represents the main antenna, and r represents the secondary antenna.
[0031] Step 3: Subtract the hardware channel delay, RF cable delay, and integer part from the carrier phase single difference measurement value to obtain the carrier phase single difference residual;
[0032] Furthermore, step 3 specifically includes:
[0033] When there is no deceptive interference signal, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: in, This represents the single-difference ambiguity, with values of integers, bcos(α). i α represents the projection length of the baseline vector onto the line-of-sight vector. i ε represents the angle between the actual signal satellite line-of-sight vector and the baseline vector. real This represents the measurement error of the actual signal;
[0034] When spoofing interference signals are present, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: Where, α spoof ε represents the angle between the deception signal satellite line-of-sight vector and the baseline vector. spoof This indicates a measurement error in the deceptive signal.
[0035] Furthermore, the formula for calculating the carrier phase single-difference residual is as follows: in, The value represents the carrier phase single-difference measurement, i represents the satellite number, u represents the main antenna, r represents the slave antenna, and Δt represents the hardware channel delay and RF cable delay.
[0036] In practice, the hardware channel delay and RF cable delay from step 1 can be deducted, collectively referred to as hardware delay Δt. Considering that the time between the two RF channels of the receiver is synchronized, therefore, in the absence of deceptive interference, the remaining portion... That is, the projection length of the baseline vector onto the line-of-sight vector, bcos(α). i ) and single-difference ambiguity sum
[0037]
[0038] In the above formula, α iε represents the angle between the actual signal satellite line-of-sight vector and the baseline vector. real This represents the measurement error of the real signal, which here is white noise following a Gaussian distribution. For spoofing signals, the remaining part... This is the projection of the baseline vector onto the line-of-sight vector of the deceiving signal source and the single-difference ambiguity. sum
[0039]
[0040] In the above formula, α spoof ε represents the angle between the deception signal satellite line-of-sight vector and the baseline vector. spoof This indicates the measurement error of the deception signal, since the deception signal source usually comes from one direction, i.e., α. spoof Since they are identical, the carrier phase single-difference measurements of each satellite are identical after deducting hardware delay and single-difference ambiguity.
[0041] Then, the carrier phase single-difference measurement value after deducting hardware delay is rounded to obtain the rounded residual. This process can eliminate single-difference ambiguity and limit the value to the range of [-0.5, 0.5).
[0042]
[0043] For real signals, since satellites are approximately uniformly distributed at the zenith, therefore The statistical properties are approximately uniformly distributed in the interval [-0.5, 0.5). For deception signals, The statistical characteristics are approximately: mean u (u∈[-0.5,0.5)) and standard deviation σ. w =2σ (σ represents the measurement accuracy of the carrier phase) normal distribution.
[0044] Step 4: Accumulate the single-difference carrier phase residual over multiple epochs to obtain the multi-epoch accumulated average residual;
[0045] Based on the above embodiments, the expression for the multi-epoch cumulative average residual is as follows: Where n is the epochal cumulative number.
[0046] In practice, the single-difference residuals obtained in step 3 are accumulated over n epochs to obtain the multi-epoch accumulated average residuals. If it is a deceptive signal, then The standard deviation further decreased, meaning the residuals of each satellite... The signal becomes more concentrated, while normal signals remain unaffected.
[0047]
[0048]
[0049] Step 5: Based on the statistical characteristics of the multi-epoch cumulative average residuals, the DBSCAN clustering algorithm is used to identify satellites with clustered residuals.
[0050] In practice, DBSCAN is a density-based clustering algorithm that can divide sufficiently high-density regions into clusters. Based on the statistical characteristics of the cumulative residual of the carrier phase single difference over multiple epochs measured by the real signal and the spoof signal in step 4, the residual of the carrier phase single difference corresponding to the spoof signal conforms to the clustering characteristics, and the DBSCAN clustering algorithm can be used to identify this part of the satellite.
[0051] Step 6: Perform a threshold test on the number of clustered satellites. Signals with a number of clustered satellites greater than the threshold are marked as deceptive signals, and the clustered satellites are marked as deceptive satellites.
[0052] In practice, based on the number of spoofed satellites identified in step 5, if it exceeds a certain threshold, it is considered that there is a spoofing interference signal, and the corresponding satellite is marked.
[0053] Analysis shows that, even when subjected to spoofing interference, this method can quickly detect the presence of spoofing signals without obtaining baseline vectors, and can effectively detect the satellites contained within the spoofing signals.
[0054] The dual-antenna carrier phase anti-spoofing detection method based on the DBSCAN clustering algorithm provided in this embodiment uses the inherent characteristic that the single-difference carrier phase measurement values between different satellites are similar when the dual antennas receive spoofing signals. By using the DBSCAN clustering method to identify this characteristic, it can effectively detect spoofing signals and remove affected satellites. Spoofing detection can be performed without obtaining the baseline vector information of the dual antennas, which improves detection efficiency and adaptability.
[0055] The units described in the embodiments of this disclosure can be implemented in software or in hardware.
[0056] It should be understood that the various parts of this disclosure can be implemented in hardware, software, firmware, or a combination thereof.
[0057] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.
Claims
1. A dual-antenna carrier phase anti-spoofing detection method based on DBSCAN clustering algorithm, characterized in that, include: Step 1: Calibrate the hardware channel delay of the two RF front-ends of the receiver connected to the antenna, and calibrate the delay of the two RF cables connected to the antenna. Step 2: Calculate the carrier phase single-difference measurement value for each satellite; Step 3: Subtract the hardware channel delay, RF cable delay, and integer part from the carrier phase single difference measurement value to obtain the carrier phase single difference residual; Step 4: Accumulate the single-difference carrier phase residual over multiple epochs to obtain the multi-epoch accumulated average residual; Step 5: Based on the statistical characteristics of the multi-epoch cumulative average residuals, the DBSCAN clustering algorithm is used to identify satellites with clustered residuals. Step 6: Perform a threshold test on the number of clustered satellites. Signals with a number of clustered satellites greater than the threshold are marked as deceptive signals, and the clustered satellites are marked as deceptive satellites.
2. The method according to claim 1, characterized in that... Step 3 specifically includes: When there is no deceptive interference signal, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: ,in, This represents the single-difference ambiguity, and its value is an integer. This represents the length of the projection of the baseline vector onto the line-of-sight vector. This represents the angle between the actual signal satellite line-of-sight vector and the baseline vector. This represents the measurement error of the actual signal. This indicates hardware channel delay and RF cable delay; When spoofing interference signals are present, the expression for subtracting hardware channel delay and RF cable delay from the carrier phase single-difference measurement value is as follows: ,in, This represents the angle between the deception signal satellite's line-of-sight vector and the baseline vector. This indicates a measurement error in the deceptive signal.
3. The method according to claim 1, characterized in that... The formula for calculating the carrier phase single-difference residual is as follows: ,in, This represents the single-difference measurement value of the carrier phase. Indicates satellite number, Indicates the main antenna. Indicates from the antenna, This indicates the hardware channel delay and the RF cable delay.
4. The method according to claim 1, characterized in that... The expression for the multi-epoch cumulative average residual is as follows: , where n is the epoch cumulative number.