A method for resisting deception interference based on the rate of change of signal power

Abstract

This invention discloses an anti-spoofing interference processing method based on the rate of change of signal power, belonging to the field of digital information processing technology for land-based navigation system receivers. The method includes the following steps: the receiver captures navigation signals and calculates the pseudorange between the receiver and each base station; the position coordinates are calculated using a least squares algorithm based on the pseudorange; crucially, by comparing the rate of change of theoretical power with that of actual power, combined with the K-means algorithm, spoofing signals are identified and eliminated, ultimately achieving accurate positioning. This invention addresses the deficiency of blind spots in anti-spoofing interference methods based on absolute power detection. It eliminates blind spots during use and requires no hardware modification to existing receivers, ensuring the positioning accuracy and reliability of the navigation receiver and enhancing the system's anti-interference capability.

Description

Technical Field

[0001] This invention belongs to the field of digital information processing technology for land-based navigation system receivers, specifically a method for anti-spoofing interference processing based on the rate of change of signal power. Background Technology

[0002] In recent years, land-based radio navigation technology has developed rapidly. As a backup navigation system when satellite navigation systems are unavailable, more and more user equipment is equipped with land-based navigation receivers. Similar to satellite navigation receivers, if a land-based navigation receiver captures and tracks a spoofing signal emitted by an interference source, it will introduce false navigation information into the positioning calculation process, resulting in incorrect results (position, velocity, and time).

[0003] Spoofing sources can receive and forward navigation signals broadcast by navigation base stations. If the receiver does not perform anti-spoofing processing on the received signals, it cannot distinguish between correct and false navigation signals. Current research on receiver anti-spoofing processing includes: signal power detection technology, signal quality detection technology, multi-antenna spoofing detection technology, inertial unit-assisted detection technology, and message encryption and authentication technology. Signal power-based and signal quality-based detection technologies have blind spots in practical applications, where the receiver cannot perform anti-spoofing interference detection. Multi-antenna-based and inertial unit-assisted detection technologies require additional hardware modifications to the receiver, resulting in high implementation costs.

[0004] Existing anti-spoofing technologies are often applied to satellite navigation receivers. However, land-based navigation systems differ from satellite navigation systems. Land-based navigation base stations are located in fixed positions on the ground, and the distance between the base station and the receiver changes as the receiver moves. The signal power of the navigation signal received by the receiver has a large dynamic range. Therefore, traditional anti-spoofing methods based on signal power are not suitable for land-based navigation receivers.

[0005] Based on this, the present invention proposes an anti-spoofing interference processing method based on the signal power change rate suitable for land-based navigation receivers. Summary of the Invention

[0006] To address the above problems, this invention provides an anti-spoofing interference processing method based on the rate of change of signal power, which solves the defect of the identification blind zone in the anti-spoofing interference method based on absolute power detection. It has no blind zone during use and does not require hardware modification to the existing receiver.

[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0008] A method for resisting deception interference based on the rate of change of signal power includes the following steps:

[0009] S1: The receiver captures and tracks the ground-based navigation signal of the base station, and obtains the signal transmission time and navigation message through bit synchronization and frame synchronization;

[0010] S2: Calculate the pseudorange between the receiver and each base station based on the signal transmission time and navigation message;

[0011] S3: The position coordinates of the coarse positioning receiver are obtained by iterative calculation using the least squares algorithm based on the pseudorange;

[0012] S4: Use a lookup table to obtain the ASF correction parameters, perform position correction, and obtain the position coordinates of the fine positioning receiver;

[0013] S5: Calculate the theoretical power of the base station signal propagating to that location based on the position coordinates of the precision positioning receiver;

[0014] S6: Based on the position coordinates of the precision positioning receiver, record the actual power of the base station signal actually received by the receiver;

[0015] S7: Continuously record the theoretical power and actual power at multiple locations, and calculate the rate of change of actual power and the rate of change of theoretical power;

[0016] S8: Calculate the sum of errors between the actual power change rate and the theoretical power change rate, use the K-means algorithm to remove false base station signals, use the pseudorange of the real base station for positioning calculation, and complete the anti-spoofing interference detection.

[0017] The beneficial effects of the above scheme are: it provides an anti-spoofing interference processing method that can effectively identify and eliminate fake base station signals, thereby ensuring the positioning accuracy and reliability of the navigation receiver and enhancing the anti-interference capability of the system.

[0018] The specific working principle of the above scheme is as follows: it achieves anti-spoofing interference through a series of steps, including capturing navigation signals, calculating pseudorange, iteratively solving position coordinates, calculating theoretical power, recording actual power, comparing power change rate, using K-means algorithm to identify and eliminate false signals, and finally completing accurate positioning calculation.

[0019] In a preferred implementation, the signal model received by the receiver in step S2 is as follows:

[0020]

[0021] in, The signal emitted by the actual base station. η(t) represents the deceptive signal emitted by the fake base station, and η(t) represents the noise introduced during reception.

[0022] The beneficial effect of the above implementation is that it provides a detailed mathematical model of the signal received by the receiver, including the real signal, spoofing signal and noise, which helps to analyze and process the received signal more accurately.

[0023] The specific working principle adopted in the above implementation is as follows: a mathematical model of the received signal is defined, which can distinguish between real base station signals, fake base station signals, and noise, thus providing a foundation for subsequent signal processing.

[0024] In a preferred implementation, the least squares algorithm uses Newton's iteration method for iterative calculations in step S3.

[0025] The beneficial effects of the above implementation are: using Newton's iteration method for iterative calculation of the least squares algorithm improves computational efficiency and accuracy, making the solution of position coordinates faster and more accurate.

[0026] The specific working principle adopted in the above implementation is as follows: when solving for the receiver position coordinates, Newton's iteration method is used to optimize the least squares method so as to quickly converge to the exact solution.

[0027] In a preferred implementation scenario, the specific steps of S4 are as follows:

[0028] Based on the receiver's coarse positioning results, the ASF correction parameters are obtained by looking up a table.

[0029] Substitute the ASF correction parameters, recalculate the pseudorange and receiver position, and obtain the precise receiver position.

[0030] The beneficial effects of step S4 are mainly reflected in the following aspects:

[0031] 1. Improve positioning accuracy: By using the ASF (Amplitude and Phase of Signal Fluctuation) correction parameter obtained by the lookup table method, the coarse positioning results can be corrected, thereby obtaining more accurate receiver position coordinates.

[0032] 2. Optimize the calculation process: The table lookup method is a fast and effective method that can reduce the amount of calculation and improve the efficiency of the location process.

[0033] 3. Adaptability: By using the lookup table method, parameters can be quickly adjusted and corrected according to different environments and conditions, making the positioning system more flexible and adaptable.

[0034] 4. Reduce errors: By applying correction parameters, errors introduced by factors such as changes in the signal propagation environment and equipment errors can be reduced, thereby improving the reliability of positioning.

[0035] The detailed principle of step S4 is as follows:

[0036] Analysis of coarse positioning results: First, the receiver obtains a preliminary position coordinate through the least squares algorithm in step S3. This coordinate is coarse and may contain some errors.

[0037] ASF correction parameters are obtained by looking up the table: Based on the coarse positioning results, the receiver queries a preset correction parameter table to obtain the ASF correction parameters related to the current positioning results. These parameters are additional secondary phase factor (time delay of navigation signal under the actual space ground wave propagation path) correction parameters, that is, time delay change parameters caused by factors such as space, season, and local environmental changes on ground wave propagation.

[0038] Application of correction parameters: The acquired ASF correction parameters are applied to the pseudorange calculation to adjust the original pseudorange. This step is to compensate for any delays or attenuation that the signal may experience during propagation.

[0039] Recalculate position: After applying the correction parameters, the receiver's position coordinates are recalculated. This step typically involves re-executing the positioning algorithm, such as using the least squares method again, but this time based on the corrected pseudorange.

[0040] Obtaining the fine positioning result: Through the above steps, a corrected and more accurate receiver position coordinate is finally obtained, which is the fine positioning result.

[0041] By implementing the S4 steps, not only is the accuracy of positioning improved, but the system's adaptability to different environmental conditions is also enhanced, thereby ensuring the reliability and effectiveness of the navigation system.

[0042] In a preferred implementation scenario, the specific steps of S5 are as follows:

[0043] Calculate the great circle distances between this location and each base station based on the receiver's location coordinates;

[0044] Calculate the theoretical signal strength of each base station signal after it propagates to this location;

[0045] Calculate the theoretical signal power density after the base station signal propagates to this location;

[0046] Calculate the theoretical signal power received by the receiver at this location;

[0047] Store the actual received power, the theoretical received power, and the great circle distance between the receiver and the base station.

[0048] The beneficial effects of the above implementation are: it provides a detailed set of steps for calculating theoretical power, ensuring the accuracy of theoretical power calculation and providing a reliable data basis for subsequent comparison of power change rates.

[0049] The specific working principle adopted in the above implementation is as follows: by calculating the great circle distance, theoretical signal field strength, power density and theoretical signal power, and storing the actual received power and related distance, the necessary data is provided for comparing the actual power and the theoretical power.

[0050] In a preferred implementation, the formula for calculating the great circle distance between the receiver and the base station in step S5 is as follows:

[0051]

[0052] in For the receiver position u = [x u ,y u ,z u ] T The corresponding latitude and longitude, The location p of base station k (k) =[x (k) ,y (k) ,z (k) ] T The corresponding latitude and longitude, where R is the Earth's radius.

[0053] The beneficial effect of the above implementation is that it provides a method for accurately calculating the great circle distance, which is crucial for subsequent calculations of theoretical power and power density.

[0054] The specific working principle adopted in the above implementation is to use the arccos function and sine and cosine functions in spherical trigonometry to calculate the great circle distance between the receiver and the base station.

[0055] In the preferred implementation, the theoretical signal power density is calculated using the following formula in step S5:

[0056]

[0057] in, Let be the theoretical signal power density of base station k received by the receiver at location u; For the transmitter's transmission frequency f k The signal is transmitted in l k Electric field strength at a distance; Let k be the transmission power of base station k. Let be the antenna gain of base station k.

[0058] The beneficial effect of the above implementation is that by clarifying the calculation method of theoretical signal power density, an accurate basis is provided for the calculation of theoretical signal power.

[0059] The specific working principle adopted in the above implementation is as follows: the theoretical signal power density is calculated based on the parameters of the receiver and the base station, including the transmission frequency, transmission distance, transmission power, antenna gain, etc.

[0060] In the preferred implementation, the theoretical signal power calculation formula in step S5 is:

[0061]

[0062] in, λ represents the theoretical signal power received by the receiver at location u from base station k; k G is the wavelength of the signal transmitted by base station k; r This represents the antenna gain of the receiver.

[0063] The beneficial effect of the above implementation is that it provides a method for calculating theoretical signal power, which is crucial for evaluating the signal strength received by the receiver and for subsequent comparison of power change rates.

[0064] The specific working principle adopted in the above implementation is: combining theoretical signal power density, wavelength and antenna gain, to calculate the theoretical signal power of the base station received by the receiver at a specific location.

[0065] In a preferred implementation, during step S7, the actual power change rate of base station k at location q The theoretical power change rate of base station k at location q The calculation formula is as follows:

[0066]

[0067] Where Q represents the location, k represents the base station, u represents the receiver's location coordinate vector, and l k,q (q=1…Q) represents the great circle distance between the receiver and the base station.

[0068] The beneficial effects of the best implementation are: it defines the calculation methods for the actual power change rate and the theoretical power change rate, providing key quantitative indicators for detecting and identifying spoofing signals.

[0069] The preferred implementation uses the following working principle: by comparing the actual power and theoretical power at continuous positions, their rate of change is calculated to provide data for subsequent error analysis and spoofing signal identification.

[0070] In a preferred implementation, the model for calculating the sum of errors εk between the actual power change rate and the theoretical power change rate of the signal broadcast by base station k in step S7 is as follows:

[0071]

[0072] The beneficial effect of the above implementation is that by calculating the total error, the difference between the actual power change rate and the theoretical power change rate can be quantified, providing an effective measure for identifying deceptive signals.

[0073] The specific working principle adopted in the above implementation is as follows: the error between the actual power change rate and the theoretical power change rate of the signal broadcast by each base station is summed to obtain the total error, which is used for subsequent identification of spoofing signals.

[0074] In a preferred implementation, step S8 employs the K-means clustering algorithm to cluster ε. k They are divided into two categories, with the category with the highest average value being the spoofing base station.

[0075] The beneficial effect of the above implementation is that using the K-means clustering algorithm to classify the total error can effectively identify the spoofing base station with the largest mean, thereby improving the accuracy of anti-spoofing interference.

[0076] The specific working principle adopted in the above implementation is as follows: the calculated total error is classified by K-means clustering algorithm to identify possible spoofing base stations so as to remove these signals in the final positioning solution.

[0077] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0078] The anti-spoofing interference method based on power change rate designed in this invention has the characteristics of low implementation complexity and high identification effectiveness, which can effectively improve the anti-spoofing capability of navigation receivers.

[0079] The anti-spoofing interference method designed in this invention has the following advantages compared with other existing anti-spoofing interference methods: it does not require a certain number of antennas, and can be implemented with a single antenna; it is simple to implement, requiring only changes at the software algorithm level, without the need to modify the receiver hardware system. Attached Figure Description

[0080] Figure 1 This is a flowchart of the present invention.

[0081] Figure 2 These are the ground wave propagation curves for electromagnetic waves of various frequencies. Detailed Implementation

[0082] To enable those skilled in the art to better understand the technical solution, the present invention will be described in detail below with reference to embodiments. The description in this part is only exemplary and explanatory, and should not be used to limit the scope of protection of the present invention in any way.

[0083] like Figure 1-2As shown, the main technical problem solved by this invention is to provide an anti-spoofing interference method based on the signal power change rate, thereby overcoming the defect of the anti-spoofing interference method based on absolute power detection having a blind spot.

[0084] Based on the principle that power varies non-linearly with distance, the receiver uses least squares to obtain the initial positioning result. An autonomous anti-spoofing detection scheme based on the power change rate is then implemented. If interference signals are detected, the navigation data containing the interference signals is removed, the positioning result is updated, and the correct position information of the receiver is obtained. The flowchart of the scheme is as follows: Figure 1 As shown.

[0085] The implementation steps of the method of the present invention are as follows:

[0086] S1: The land-based navigation receiver acquires and tracks the land-based navigation signal. After acquisition and tracking are completed, the signal transmission time and navigation message are obtained through bit synchronization and frame synchronization.

[0087] S2: Based on the signal transmission time and navigation message obtained in S1, the pseudorange ρ between the receiver and each base station is calculated. k ;

[0088] S3: The pseudorange ρ between the receiver and each base station obtained in S2 k Substituting the values ​​into the least squares algorithm for iterative calculation, we obtain the coarse positioning coordinates of the receiver: uc = [x...]. uc ,y uc ,z uc ] T ;

[0089] S4: Based on the coarse positioning coordinates obtained in S3, look up the ASF correction parameters in the table, perform position correction, and obtain the fine positioning coordinates u = [x] of the fine positioning receiver. u ,y u ,z u ] T ASF represents the additional secondary phase factor, representing the time delay under the actual land propagation path.

[0090] S5: Based on the receiver's position coordinates u calculated in S4, calculate the theoretical power of the navigation signal broadcast by base station k reaching this position.

[0091] S6: Based on the receiver's position coordinates u calculated in S4, record the actual power of the navigation signal actually received by the receiver at this position from the base station k.

[0092] S7: Record the theoretical power obtained from S4 at Q consecutive positions. Record the actual power obtained by S5 at Q consecutive positions. Calculate the changes in theoretical power and actual power respectively. and

[0093] S8: Calculate the total error ε between the actual power change rate and the theoretical power change rate of the signal broadcast by base station k. k Then, the K-means algorithm is used to remove signals from fake base stations, and finally, the pseudorange of real base stations is used for positioning calculation to complete the anti-spoofing interference detection.

[0094] The specific implementation method is as follows:

[0095] S1-S2:

[0096] The signal model emitted by a land-based navigation base station is as follows:

[0097]

[0098] Where A represents the signal amplitude, C(·) represents the pseudo-random code, D(t) represents the navigation message, and f is the carrier frequency. This refers to the carrier phase.

[0099] The signal model received by the receiver is as follows:

[0100]

[0101] in, The signal emitted by the actual base station. The signal is a deception signal emitted by a fake base station, and η(t) is the noise introduced during reception, which is generally considered to be additive white Gaussian noise.

[0102] By analyzing the navigation message data contained in the received signal r(t), the pseudorange ρ between the receiver and each base station can be obtained. k (k=1…N+M), including real base station pseudorange and fake base station pseudorange, as shown in Table 1.

[0103] Table 1: Receiver Coarse Positioning Pseudorange Data Record

[0104]

[0105]

[0106] S3:

[0107] After obtaining the coarse positioning pseudorange, the positioning equations can be listed as follows:

[0108]

[0109] Where K = N + M is the total number of real and fake base stations received. p is the unknown receiver position coordinate vector. (k) =[x (k) ,y (k) ,z (k) ] T Let k be the location coordinate vector of base station k.

[0110] The receiver position in the above equation is solved using the least squares method through Newton's iteration, thus obtaining the receiver's position coordinate vector u = [x u ,y u ,z u ] T As shown in Table 2.

[0111] Table 2: Coarse Positioning Receiver Coordinates

[0112] Serial Number X-coordinate (longitude) Y-coordinate (latitude) Z-coordinate (height) 1 114.87885012 35.04965606 65.32

[0113] S4:

[0114] After obtaining the coarse location receiver position, ASF correction is performed by referring to a table. The corrected pseudorange between the receiver and each base station can be obtained, including the pseudorange of the real base station and the pseudorange of the fake base station, as shown in Table 3.

[0115] Table 3: Receiver Precision Positioning Pseudorange Data Record

[0116] Serial Number Base station number <![CDATA[Receiver pseudorange ρ k (m)]]> 1 1 77004 2 2 53428 3 3 96706 4 4 64090

[0117] S5-S6:

[0118] After obtaining the precise positioning pseudorange, the positioning equations can be listed as follows:

[0119]

[0120] Where K = N + M is the total number of real and fake base stations received. p is the unknown receiver position coordinate vector. (k) =[x (k) ,y (k) ,z (k) ] T Let k be the location coordinate vector of base station k.

[0121] The receiver position in the above equation is solved using the least squares method through Newton's iteration, thus obtaining the receiver's position coordinate vector u = [x u ,y u ,z u ] T As shown in Table 4.

[0122] Table 4: Receiver Precision Position Coordinates

[0123] Serial Number X-coordinate (longitude) Y-coordinate (latitude) Z-coordinate (height) 1 114.87412262 34.70392900 64.21

[0124] Calculate the great circle distance l between this location and each base station. k Then, the theoretical signal strength of each base station signal after propagation to this location is calculated. Specifically, it is expressed as follows:

[0125]

[0126] in For the receiver position u = [x u ,y u ,z u ] T The corresponding latitude and longitude, The location p of base station k (k) =[x (k) ,y (k) ,z (k) ] T The corresponding latitude and longitude, where R is the Earth's radius. Let k be the transmission power of base station k. Let k be the antenna gain of base station k. For a 1kW transmitter, the transmission frequency f k The signal is transmitted in l k The field strength at a distance, and the ground wave propagation curves for signals of various frequencies are as follows: Figure 2 As shown.

[0127] Furthermore, the theoretical signal power density after the base station k signal propagates to this location can be obtained. and the theoretical signal power received by the receiver here. Specifically, it is expressed as follows:

[0128]

[0129] Where, λ k G is the wavelength of the signal transmitted by base station k. r This represents the antenna gain of the receiver.

[0130] Thus, we can obtain the receiver's position u = [x] u ,y u ,z u ] T Theoretical received power

[0131] Furthermore, the actual received power at this time and theoretical received power and the great circle distance l between the receiver and the base station k Store it.

[0132] Table 5: Record of Theoretical Power and Actual Power Data

[0133]

[0134]

[0135] S7:

[0136] During the receiver's movement, record the actual received power at Q consecutive positions. Theoretical received power And the corresponding great circle distance l between the receiver and the base station k,q (q=1…Q).

[0137] Furthermore, calculate the actual power change rate. and theoretical power change rate The results are shown in Table 6 below:

[0138]

[0139] Table 6: Power Change Rate Data Record

[0140]

[0141] S8:

[0142] Furthermore, the sum of errors ε between the actual power change rate and the theoretical power change rate of the signal broadcast by base station k is calculated. k The results are shown in Table 7:

[0143]

[0144] Table 7: Total Error Data Record

[0145] Serial Number Base station number <![CDATA[Total error ò k > 1 1 0.33 2 2 0.34 3 3 0.11 4 4 122.38

[0146] Furthermore, the K-means clustering algorithm is used to cluster ε k They are divided into two categories, with the category with the highest mean being spoofing base stations. This distinguishes between real and fake base stations, as shown in Table 8.

[0147] Table 8: K-means Clustering Results

[0148] Cluster number Category Description Base station number 1 real base station 1,2,3 2 Deceiving base stations 4

[0149] Finally, fake base stations are eliminated, and the pseudorange corresponding to the real base stations is used for receiver positioning calculation.

[0150] This concludes the anti-spoofing detection process based on power change rate.

[0151] The detection rates of the method of this invention and the traditional method are compared in the table below:

[0152] Comparison items Method of the present invention Traditional methods Detection success rate 95％ 80％

[0153] It should be noted that, in this document, the terms "comprising," "including," and any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Specific examples have been used in this document to illustrate the principles and implementation methods of the present invention. These examples are merely for the purpose of helping to understand the method and core ideas of the present invention. The above descriptions are only preferred embodiments of the present invention. It should be pointed out that, due to the limitations of written expression and the objective existence of infinite specific structures, those skilled in the art can make several improvements, modifications, or variations without departing from the principles of the present invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, variations, or combinations, or the direct application of the concept and technical solution of the present invention to other situations without modification, should all be considered within the scope of protection of the present invention.

Claims

1. A method for anti-spoofing interference processing based on signal power change rate, characterized in that, Includes the following steps: S1: The receiver captures and tracks the ground-based navigation signal of the base station, and obtains the signal transmission time and navigation message through bit synchronization and frame synchronization; S2: Calculate the pseudorange between the receiver and each base station based on the signal transmission time and navigation message; S3: Calculate the receiver's position coordinates iteratively using the least squares algorithm based on the pseudorange; S4: Use the lookup table method to obtain the additional secondary phase factor ASF correction parameter, perform position correction, and obtain the position coordinates of the fine positioning receiver; S5: Calculate the theoretical power of the base station signal propagating to that location based on the receiver's location coordinates; The specific steps are as follows: a. Calculate the great circle distances between this location and each base station based on the receiver's location coordinates; b. Calculate the theoretical signal strength of each base station signal after it propagates to this location; c. Calculate the theoretical signal power density after the base station signal propagates to this location; d. Based on the parameters obtained in step bc, calculate the theoretical signal power received by the receiver at this point; e. Store the actual received power and theoretical received power at this time, as well as the great circle distance between the receiver and the base station; S6: Based on the receiver's location coordinates, record the actual power of the base station signal actually received by the receiver; S7: Continuously record the theoretical power and actual power at multiple locations, and calculate the rate of change of actual power and the rate of change of theoretical power; S8: Calculate the sum of errors between the actual power change rate and the theoretical power change rate, use the K-means algorithm to remove false base station signals, use the pseudorange of the real base station for positioning calculation, and complete the anti-spoofing interference detection.

2. The anti-spoofing interference processing method based on signal power change rate according to claim 1, characterized in that, In step S2, the signal model received by the receiver is as follows: in, The signal emitted by the actual base station. These are deceptive signals emitted by fake base stations. This refers to the noise introduced during reception.

3. The method according to claim 1, characterized in that, In step S3, the iterative calculation of the least squares algorithm uses Newton's iteration method.

4. The method according to claim 1, characterized in that, In step S5, the formula for calculating the great circle distance between the receiver and the base station is: in For receiver position The corresponding latitude and longitude, For base stations Location Corresponding latitude and longitude The radius is the Earth's radius.

5. The method according to claim 4, characterized in that, In step S5, the theoretical signal power density is calculated using the following formula: in, Let be the theoretical signal power density of base station k received by the receiver at location u; For the transmitter's transmission frequency Signal in transmission Electric field strength at a distance; For base stations The transmission power, For base stations Antenna gain.

6. The method according to claim 1, characterized in that, In step S5, the theoretical signal power calculation formula is as follows: in, This represents the theoretical signal power received by the receiver from base station k at location u. For base stations The wavelength of the transmitted signal; This represents the antenna gain of the receiver.

7. The anti-spoofing interference processing method based on signal power change rate according to claim 1, characterized in that, In step S7, the actual power change rate of base station k at location q The theoretical power change rate of base station k at location q The calculation formula is as follows: Where Q represents the location, k represents the base station, and u represents the receiver's location coordinate vector. This represents the great circle distance between the receiver and the base station.

8. The anti-spoofing interference processing method based on signal power change rate according to claim 6, characterized in that, In step S7, the base station is calculated. The sum of errors between the actual rate of change of the broadcast signal power and the theoretical rate of change of the broadcast signal. The model is as follows: 。 9. The anti-spoofing interference processing method based on signal power change rate according to claim 1, characterized in that, In step S8, the K-means clustering algorithm is used to... They are divided into two categories, with the category with the highest average value being the spoofing base station.

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