A satellite navigation spoofing source searching method based on Chan algorithm

Abstract

The application discloses a satellite navigation deception source searching method based on Chan algorithm and belongs to the field of electronic countermeasures. The application utilizes deception perception nodes distributed in a monitoring area to alarm and monitor a current satellite navigation signal environment, calculates pseudo-range observation information of deception jamming signals and real navigation signals, and transmits the pseudo-range observation information to a central processing station to distinguish the deception jamming signals from the real navigation signals. Then, the Chan algorithm is used to perform signal arrival time difference positioning on the pseudo-range observation information of all the deception jamming signals, so as to calculate the positions of the deception sources, thereby realizing the searching and positioning of the navigation deception sources. The application can be used for interference monitoring and protection of key application stations of satellite navigation, and can improve the safety and reliability of satellite navigation equipment in safety-sensitive fields. The method is simple, easy to realize and has a high application prospect.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of electronic countermeasures, and particularly to a satellite navigation deception source searching method based on Chan algorithm. BACKGROUND

[0002] With the construction and improvement of Beidou-3 satellite navigation system, satellite navigation equipment has been rapidly applied in many safety-sensitive fields such as civil aviation, power grid and railway transportation. However, due to the openness and openness of satellite navigation civilian signals, it is simple and feasible to implement satellite navigation deception jamming by forging satellite navigation signals.

[0003] In addition, unlike other electromagnetic interference, satellite navigation deception jamming can take effect when the power is lower than the noise floor, so it is difficult to be detected by general electromagnetic spectrum detection equipment. In order to protect the application of satellite navigation equipment in safety-sensitive fields, it is necessary to establish a detection system for satellite navigation deception sources. However, there is no such technical solution in the prior art. SUMMARY

[0004] Therefore, the present application provides a satellite navigation deception source searching method based on Chan algorithm. The present application uses the signal arrival time difference based on Chan algorithm to locate the navigation deception jamming source, fills the gap in the field of navigation deception jamming source detection in China at present, and the method is simple and easy to implement, and has high engineering value.

[0005] The purpose of the present application is achieved as follows:

[0006] A satellite navigation deception source searching method based on Chan algorithm, comprising the following steps:

[0007] (1) deploying deception perception nodes, placing the receiving antennas of the deception perception nodes around the area monitored by the navigation deception jamming, and calibrating the actual coordinates of the receiving antennas;

[0008] (2) starting the deception perception nodes, and injecting the actual coordinates of the receiving antennas into the deception perception nodes;

[0009] (3) the deception perception nodes continuously search for navigation deception jamming and real navigation signals in the space in the code / frequency two-dimensional domain;

[0010] (4) the deception perception nodes perform signal despreading processing on all the searched signals, and transmit the extracted pseudo-range observations to the central processing station;

[0011] (5) the central processing station distinguishes the deception jamming and the real navigation signals from the observations transmitted back by the deception perception nodes;

[0012] (6) The central processing station collects the pseudo-range observations transmitted by each spoofing-aware node, and calculates the position of the spoofing jammer by Chan algorithm to obtain the position of the navigation spoofing jammer.

[0013] Further, the specific manner of step (3) is:

[0014] The spoofing-aware node searches the PRN code of all currently visible stars in the code / frequency two-dimensional domain, and when there are two correlation peaks in a PRN code, it indicates that there is currently spoofing jamming.

[0015] Further, the specific manner of step (4) is:

[0016] The spoofing-aware node continuously tracks each correlation peak signal, calculates the corresponding pseudo-range observation, and transmits the pseudo-range observation calculated by each correlation peak signal to the central processing station.

[0017] Further, the specific manner of step (5) is:

[0018] (501) For the satellite signal searched by the spoofing-aware node x that exists spoofing jamming, the pseudo-range observations corresponding to the two correlation peaks in it are respectively taken as the reference, and the pseudo-range observations corresponding to the correlation peaks in the satellite signal of the same satellite searched by other spoofing-aware nodes k are subtracted to obtain four pseudo-range differences:

[0019]

[0020] Wherein, the superscript PRN is the PRN code of the satellite, used to identify the satellite, the subscript k is the number of the spoofing-aware node, the subscript x represents the spoofing-aware node as the reference, k≠x, and the subscript of PRN is the correlation peak number in the signal of the satellite PRN, represents the pseudo-range observation of the i-th correlation peak in the signal of the satellite PRN received by the spoofing-aware node k, i=1 or 2;

[0021] (502) The position of the satellite PRN is calculated according to the satellite ephemeris, and then the pseudo-range difference of the real signal of the satellite PRN to the spoofing-aware node x and the spoofing-aware node k is calculated according to the position of the satellite PRN and the known positions of the spoofing-aware node x and the spoofing-aware node k

[0022] (503) Find the pseudo-range difference that is not more than 10 meters from the pseudo-range difference in the four pseudo-range differences calculated in step (501), and the two correlation peaks corresponding to the pseudo-range difference are the correlation peaks of the real signal;

[0023] (504)Repeat steps (501) to (503) to distinguish the real signals and the spoofed signals in all the satellite signals with spoofing interference.

[0024] Further, the specific way of step (6) is:

[0025] (601)Using the pseudo-range observation of the real signals, the receiving antenna position of each spoofing perception node is calculated to obtain the receiving antenna position (X n ,Y n ,Z n ) of each spoofing perception node and the clock difference δ n of each spoofing perception node, where n is the spoofing perception node serial number.

[0026] (602)The distance R n between the target spoofing source (x, y, z) and the nth spoofing perception node is calculated.

[0027]

[0028] (603)Taking the distance R1 between the first spoofing perception node and the target spoofing source as the reference, the distances R n between the other spoofing perception nodes and the target spoofing source are subtracted from R1 to obtain the difference R n,1 .

[0029]

[0030] (604)After squaring the formula in step (603) and expanding, we obtain:

[0031]

[0032] And:

[0033]

[0034] Where X n,1 =X n -X1, Y n,1 =Y n -Y1, Z n,1 =Z n -Z1.

[0035] In matrix form, it is represented as H=G*P, where:

[0036]

[0037] The error vector is Ψ=H-GP=c*B*n+0.5*c 2 *n, and the covariance matrix is:

[0038]

[0039] Wherein, Q is the covariance matrix of measurement noise;

[0040] (605) The formula of step (603) is operated by using one-time least square method, and the following formula is obtained:

[0041]

[0042] (606) Let P11=x 0 +e1, P12=y 0 +e2, P13=z 0 +e3, e1…e4 represent estimation errors, and the error vector Ψ'=H'-G'P'=2*B'*Δp, wherein:

[0043]

[0044] The covariance matrix is:

[0045]

[0046] (607) The formula in step (606) is operated by using one-time least square method again, and the following formula is obtained:

[0047]

[0048] (x', y', z') is the final positioning target deception source position.

[0049] The present application has the following beneficial effects:

[0050] 1. Compared with the traditional suppression jamming, the satellite navigation deception jamming has the characteristics of low transmitting power and high concealment, which causes great difficulty in monitoring and positioning of the satellite navigation deception jamming. The present application proposes a method for finding and searching the satellite navigation deception jamming according to the characteristics of the satellite navigation deception jamming, and lays a technical foundation for the development of the satellite navigation deception jamming defense system for the satellite navigation application safety sensitive site.

[0051] 2. The present application provides a method for fast alarming and deception source positioning of the navigation deception jamming, which is suitable for the protection of the satellite navigation application key site (for example, airport, power grid, communication gateway station, etc.) with high safety requirement.

[0052] 3、The present application analyzes the spoofing interference pseudo-range parameters returned by the spoofing sensing nodes distributed in a certain range, and calculates the specific position of the satellite navigation spoofing source by using the Chan algorithm based on the time difference of signal arrival by differencing the spoofing interference pseudo-range obtained by each spoofing sensing node, thereby realizing the reverse positioning of the spoofing interference source. This method draws lessons from the signal arrival time method in the field of radio interference monitoring, is suitable for the field of reverse positioning of navigation spoofing interference sources, fills the gap in the domestic radio detection and countermeasure capability for satellite navigation spoofing interference sources, and can improve the technical capability of satellite navigation countermeasures.

[0053] 4、The present application uses the feature that the propagation time delay is different when each spoofing sensing node receives the navigation spoofing interference signal, calculates the position of the spoofing interference source by using the Chan algorithm based on the time difference of the spoofing interference signals received by each spoofing interference device, and has the characteristics of simple implementation, high spoofing alarm accuracy, high spoofing source positioning accuracy, and fast speed, and has great engineering feasibility. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 The application scenario of the embodiment of the present application is shown in the figure.

[0055] Figure 2 The principle diagram of the spoofing interference identification method of the present application is shown in the figure. DETAILED DESCRIPTION

[0056] The present application will be further described below with reference to the accompanying drawings.

[0057] Taking a spoofing alarm and monitoring system composed of five spoofing sensing nodes and a central processing station as an example, the system composition and signal environment are shown in the figure. Figure 1 The five spoofing sensing nodes are deployed around the monitoring area, and continuous spoofing interference search is carried out. Since there is still a real navigation signal in the current environment, it is necessary to distinguish and identify the real navigation signal and the spoofing interference, and then separate the real navigation signal and the spoofing interference. Then, the spoofing interference node uses the real navigation signal for positioning and timing, realizes the time synchronization of each spoofing sensing node in the whole system, and finally transmits the monitoring information of the spoofing interference to the central processing station for time difference positioning based on the Chan algorithm, and calculates the position of the spoofing source.

[0058] As shown in the figure, Figure 2 A satellite navigation spoofing source searching method based on Chan algorithm includes the following steps:

[0059] (1) Deploy spoofing sensing nodes, place the receiving antennas of the spoofing sensing nodes around the area where the navigation spoofing interference is monitored, and calibrate the actual coordinates of the receiving antennas;

[0060] (2) The spoofing awareness node is powered on, and the actual coordinates of the receiving antenna are injected into the spoofing awareness node;

[0061] (3) The spoofing awareness node continuously searches for navigation spoofing interference and real navigation signals in the code-frequency two-dimensional domain in space; specifically, the spoofing awareness node performs code / frequency two-dimensional domain searching on the PRN codes of all currently visible stars, and when there are two correlation peaks in a PRN code, it indicates that there is currently spoofing interference;

[0062] (4) The spoofing awareness node performs signal despreading processing on all the searched signals, and transmits the extracted pseudorange observations to the central processing station; specifically, the spoofing awareness node continuously tracks each correlation peak signal, calculates the corresponding pseudorange observation, and transmits the pseudorange observation calculated by each correlation peak signal to the central processing station;

[0063] (5) The central processing station distinguishes which is spoofing interference and which is a real navigation signal in the observations transmitted back by the spoofing awareness node; the specific method is:

[0064] (501) For the satellite signal searched by the spoofing awareness node x that exists spoofing interference, the pseudorange observations corresponding to the two correlation peaks in it are respectively taken as the reference, and the pseudorange observations corresponding to the correlation peaks in the satellite signal of the same satellite searched by other spoofing awareness nodes k are subtracted, to obtain four pseudorange differences:

[0065]

[0066] wherein the superscript PRN is the PRN code of the satellite, used to identify the satellite, the subscript k is the number of the spoofing awareness node, the subscript x represents the spoofing awareness node as the reference, k≠x, and the subscript of PRN is the correlation peak number in the signal of the satellite PRN, represents the pseudorange observation of the spoofing awareness node k receiving the i-th correlation peak in the signal of the satellite PRN, i=1 or 2;

[0067] (502) The position of the satellite PRN is calculated according to the satellite ephemeris, and then the real signal pseudorange difference of the satellite PRN to the spoofing awareness node x and the spoofing awareness node k is calculated according to the position of the satellite PRN and the known positions of the spoofing awareness node x and the spoofing awareness node k

[0068] (503) Find the one that is not more than 10 meters different from the pseudorange difference in the four pseudorange differences calculated in step (501), and the two correlation peaks corresponding to the pseudorange difference are the correlation peaks of the real signal;

[0069] (504) Repeat steps (501) to (503) to distinguish the real signals and the spoofed signals in all the satellite signals with spoofing interference;

[0070] (6) The central processing station collects the pseudo-range observations transmitted by each spoofing awareness node, and calculates the position of the spoofing interference source through Chan algorithm, so as to obtain the position of the navigation spoofing interference source; the specific method is as follows:

[0071] (601) The pseudo-range observations of the real signals are used to calculate the position of the receiving antenna of each spoofing awareness node, so as to obtain the position (X n ,Y n ,Z n ) of the receiving antenna of each spoofing awareness node and the clock difference δ n of each spoofing awareness node, wherein n is the serial number of the spoofing awareness node;

[0072] (602) The distance R n between the target spoofing source (x, y, z) and the n-th spoofing awareness node is calculated:

[0073]

[0074] (603) The distance R n between the target spoofing source and the n-th spoofing awareness node is calculated, and the distance R n,1 between the target spoofing source and the 1st spoofing awareness node is taken as the reference, so that the difference R n,1 between the distance R n and the distance R n,1 is obtained:

[0075]

[0076] (604) The formula in step (603) is squared and expanded, so as to obtain:

[0077]

[0078] and:

[0079]

[0080] wherein X n,1 =X n -X1, Y n,1 =Y n -Y1, Z n,1 =Z n -Z1;

[0081] which is expressed in the matrix form as H=G*P, wherein:

[0082]

[0083] The error vector is Ψ = H - GP = c * B * n + 0.5 * c 2 n, whose covariance matrix is:

[0084]

[0085] Wherein, Q is the covariance matrix of measurement noise;

[0086] (605) The formula of step (603) is operated by one time least square method, and the following formula is obtained:

[0087]

[0088] (606) Let P11 = x 0 + e1, P12 = y 0 + e2, P13 = z 0 + e3, e1…e4 represent estimation errors, and the error vector Ψ' = H' - G' P' = 2 * B' * Δp, wherein:

[0089]

[0090] The covariance matrix is:

[0091]

[0092] (607) The formula in step (606) is operated by one time least square method again, and the following formula is obtained:

[0093]

[0094] (x', y', z') is the finally located target spoofing source position.

[0095] The method is crucial in distinguishing the real navigation signal from the spoofing interference. Since the transmitting antenna of all the spoofing interferences is one, the pseudo-range differences of all the nodes obtained by the spoofing interferences are the same, while the pseudo-range differences of all the nodes obtained by the real signal are quite different.

[0096] In summary, the present application utilizes the spoofing-aware nodes distributed in the monitoring area to alarm and monitor the current satellite navigation signal environment, calculates the pseudo-range observation information of the spoofing interference signal and the real navigation signal, and transmits the pseudo-range observation information to the central processing station for distinguishing the spoofing interference signal from the real navigation signal, and then uses the Chan algorithm to perform signal arrival time difference positioning on the pseudo-range observation information of all the spoofing interference signals, and calculates the position of the spoofing source, so as to realize the search and positioning of the navigation spoofing source. The present application can be used for interference monitoring and protection of satellite navigation key application stations, and improves the security and reliability of satellite navigation equipment in security-sensitive fields. The method of the present application is simple and easy to implement, and has a high application prospect.

Claims

1. A method for searching satellite navigation spoofing sources based on the Chan algorithm, characterized in that, Includes the following steps: (1) Deploy deception sensing nodes, place the receiving antennas of the deception sensing nodes around the area of ​​domain monitoring navigation deception interference, and mark the actual coordinates of the receiving antennas; (2) The deception sensing node is powered on, and the actual coordinates of the receiving antenna are injected into the deception sensing node; (3) The deception sensing node continuously searches for navigation deception interference and real navigation signals in the code / frequency two-dimensional domain; the specific method is as follows: The deception sensing node performs a code / frequency two-dimensional domain search on the PRN codes of all currently visible stars. When there are two correlation peaks in a PRN code, it indicates that deception interference is present. (4) The deception sensing node performs signal despreading on all the searched signals and transmits the extracted pseudorange observations to the central processing station; the specific method is as follows: The deception sensing node continuously tracks and processes each relevant peak signal, calculates the corresponding pseudorange observation, and transmits the pseudorange observation calculated for each relevant peak signal to the central processing station. (5) The central processing station distinguishes between deception interference and genuine navigation signals from the observations transmitted back from the deception sensing nodes; specifically: (501) For satellite signals with deception interference searched by deception sensing node x, the pseudorange observations corresponding to the two correlation peaks are used as the benchmark, and the pseudorange observations corresponding to the correlation peaks of the same satellite signals searched by other deception sensing nodes k are subtracted to obtain four pseudorange differences: Among them, superscript The PRN code is used to identify the satellite. The subscript k is the number of the spoofing sensing node, and the subscript x represents the spoofing sensing node used as the reference. k ≠ x. The subscript for satellite The relevant peak numbers in the signal, Represents a deception perception node Received satellite The pseudorange observation of the i-th correlation peak in the signal, i=1 or 2; (502) Calculate the satellite's ephemeris data. The location, and then based on the satellite Based on the location of the satellite and the known locations of deception sensing nodes x and k, the satellite's position is calculated. The pseudorange difference between the real signal and the deception sensing node x and the deception sensing node k ; (503) Find the pseudo-range difference among the four pseudo-range differences calculated in step (501). The pseudo-range difference that is no more than 10 meters apart, and the two correlation peaks corresponding to this pseudo-range difference are the correlation peaks of the real signal; (504) Repeat steps (501) to (503) to distinguish the real signals and spoofed signals in all satellite signals with spoofing interference; (6) The central processing station summarizes the pseudorange observations transmitted by each deception sensing node and uses the Chan algorithm to calculate the location of the deception interference source to obtain the location of the navigation deception interference source.

2. The satellite navigation spoofing source search method based on the Chan algorithm according to claim 1, characterized in that, The specific method for step (6) is as follows: (601) Using the pseudorange observation of the real signal, the position of the receiving antenna of each deception sensing node is calculated to obtain the position of the receiving antenna of each deception sensing node. and the clock difference of each deception perception node. ,in To deceive the perception node sequence number; (602) Calculate the source of target deception With the Distance between deception perception nodes : (603) The distance between the first deception sensing node and the target deception source Based on the distance between other deception sensing nodes and the target deception source Take the difference between each pair of pairs to get the difference value. : (604) Squaring and expanding the expression in step (603), we get: And there are: in , , , ; Represented in matrix form as ,in: ， ， ， The error vector is Its covariance matrix is: ， in, The covariance matrix of the measurement noise; (605) Applying the first least squares method to the expression in step (603), we get: (606) Order , , , , To represent the estimation error, the error vector... ,in: ， ， ， ， Its covariance matrix is: ； (607) Perform the least squares operation on the expression in step (606) again to obtain: This is the final location of the target deception source.

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