GNSS deception interference detection method and device based on signal direction vector autocorrelation

Abstract

The present invention discloses a GNSS deception interference detection method and device based on signal direction vector autocorrelation, which relates to the field of satellite navigation technology. The method includes: storing and updating the direction vectors corresponding to each satellite signal and arranging them into a matrix; multiplying the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix; calculating the modulus and phase values ​​of all elements of the autocorrelation matrix, and calculating the 1-norm or infinity-norm of the autocorrelation matrix based on the modulus; and judging whether the current satellite signal contains a deception signal based on the 1-norm, infinity-norm or phase value of the autocorrelation matrix. The method provided by the present invention not only enhances and clarifies the role of collaborative detection between multiple satellite signals and improves the accuracy of detection, but also the detection results can be quantified, and the threshold value is easy to set.

Description

Technical Field

[0001] The present invention relates to the field of satellite navigation technology, and more specifically, to a GNSS deception interference detection method and device based on signal direction vector autocorrelation. Background Art

[0002] Satellite navigation systems are vulnerable to spoofing in certain scenarios, causing receiver positioning results to appear normal while actually deviating from their true location. This can lead to serious consequences, such as loss of control or collisions with drones and other vehicles. Deceptive jamming can be broadly categorized into generation and forwarding methods, or asynchronous and synchronous methods, depending on how it is implemented.

[0003] Detection methods for spoofing interference can be broadly categorized into signal domain, information domain, and spatial domain based on different characteristic dimensions. Signal domain detection primarily relies on changes in signal statistical power, acquisition, and tracking correlation peaks; information domain detection primarily relies on changes in Doppler, pseudorange, positioning, velocity, and clock error measurements; and spatial domain detection primarily relies on the different characteristics of the incident directions between the real satellite signal and the spoofing signal. While there is currently extensive research on the first two types of detection methods, they are unable to address more advanced synchronous spoofing. Synchronous spoofing, based on the detected target position and velocity, generates a spoofed signal synchronized with the real signal, preventing significant jumps in parameters as the spoofed signal enters the target receiver. Spatial domain feature detection does not rely on jumps in measured values, but instead considers the spatial characteristics inherent in the actual satellite distribution and the centralized transmission or forwarding of spoofed signals by the spoofing source. Therefore, it is applicable to all types of spoofing, including generation and forwarding, as well as asynchronous and synchronous spoofing.

[0004] Detecting the spatial domain features of a signal usually requires indirectly or directly obtaining the direction vector of the signal, and then identifying the authenticity of the signal based on the following features:

[0005] ① No deception interference. Usually, different satellite signals are incident from different directions, and their direction vectors are not equal to each other. The direction vector corresponding to each satellite is consistent with the direction corresponding to the satellite position calculated by the ephemeris solution, which is shown in the following formula:

[0006]

[0007] i,j∈(1,2,…N,i≠j). Among them, and They represent the elevation angle and azimuth angle of the satellite position relative to the receiving end calculated by ephemeris.

[0008] ② There is deceptive interference. The deceptive source directly generates or forwards false signals, which can cause the direction vectors of different satellite signals to be essentially the same. At the same time, the measured direction vector is often inconsistent with the direction corresponding to the satellite position calculated through the ephemeris solution. This is shown in the following formula:

[0009]

[0010] This indicates that the different satellite signals tracked come from the same direction, which means that the signal received is a false signal sent by a deceptive source.

[0011] The principle of the above detection method is relatively clear, but in the actual calculation process, it is necessary to perform difference detection one by one to check consistency or difference. The synergy between all satellite signals in the entire calculation process is unclear, and the quantification and threshold of the detection results also lack support. Summary of the Invention

[0012] To address the aforementioned technical issues, the present invention provides a GNSS spoofing jamming detection method and device based on signal directional vector autocorrelation. Based on matrix operations, this method performs autocorrelation on the directional vectors of individual satellite signals. By detecting the amplitude or phase of the autocorrelation matrix elements, the authenticity of received satellite signals can be identified. This detection process enhances the synergy between satellite signals and improves detection accuracy. Furthermore, the detection results are quantified, making it easier to determine threshold values.

[0013] In a first aspect, the present invention provides a GNSS spoofing interference detection method based on signal direction vector autocorrelation, the method comprising:

[0014] The direction vectors corresponding to each satellite signal are stored and updated, and arranged into a matrix;

[0015] Multiplying the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix;

[0016] Calculating the modulus and phase value of each element of the autocorrelation matrix, and calculating the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus;

[0017] Whether the current satellite signal contains a deception signal is determined based on the 1-norm or the infinity-norm of the autocorrelation matrix or the phase value of the element.

[0018] Furthermore, the direction vectors corresponding to the satellite signals are stored and updated, and arranged into a matrix, which is represented as follows:

[0019]

[0020] Where A represents the matrix, M is the dimension, which is the same as the number of array elements, and N is the number of satellite signals tracked. represents a complex set, and Represent the direction vectors of the first, second and Nth satellite signals respectively, They respectively represent the elevation angle and azimuth angle of the satellite signal reaching the receiving end.

[0021] Furthermore, the autocorrelation matrix is ​​obtained by multiplying the matrix by the conjugate transpose of the matrix using the following formula:

[0022] R AA =A H A

[0023] Where R AA represents the autocorrelation matrix, A H represents the conjugate transpose of a matrix, and A represents a matrix.

[0024] Furthermore, the autocorrelation matrix is ​​expressed as:

[0025]

[0026] In the formula, e represents the natural constant, m represents the array element number, j represents the imaginary unit, represents the phase shift of the received signal of each array element corresponding to the i-th satellite; where i == 1, 2..., N.

[0027] Furthermore, after multiplying the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix, the method includes:

[0028] Whether deceptive interference exists is determined based on the amplitude and phase characteristics of the autocorrelation matrix elements, and if deceptive interference exists, the modulus and phase values ​​of the autocorrelation matrix are calculated.

[0029] Furthermore, determining whether deceptive interference exists based on the amplitude and phase characteristics of the autocorrelation matrix elements includes:

[0030] If the modulus of each element in the autocorrelation matrix approaches the dimension and / or the corresponding phase angle of each element in the autocorrelation matrix approaches 0, it is determined that deceptive interference exists.

[0031] Furthermore, based on the 1-norm or the infinity-norm of the autocorrelation matrix, the following method is used to determine whether the current satellite signal contains a deceptive signal:

[0032] Determine a threshold value Γ = (M-1)N, where M is the dimension, which is the same as the number of array elements, and N is the number of tracked satellite signals;

[0033] If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​less than a threshold value, determining that the current satellite signal is a real signal;

[0034] If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​greater than or equal to a threshold value, it is determined that a deception signal exists in the current satellite signal.

[0035] Furthermore, based on the phase values ​​of the autocorrelation matrix elements, it is determined whether the current satellite signal contains a spoofing signal by the following method:

[0036] If the phase value of the autocorrelation matrix element approaches 0 and ±π, it is determined that the current satellite signal is a real signal;

[0037] If the phase value of the autocorrelation matrix element only approaches 0, it is determined that a deception signal exists in the current satellite signal.

[0038] In a second aspect, the present invention provides a GNSS spoofing interference detection device based on signal direction vector autocorrelation, the device comprising:

[0039] The satellite signal direction vector cache module is configured to store and update the direction vectors corresponding to each satellite signal and arrange them into a matrix;

[0040] An autocorrelation matrix operation module is configured to multiply the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix;

[0041] an amplitude and phase calculation module, configured to calculate the modulus and phase values ​​of the autocorrelation matrix elements, and calculate the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus;

[0042] The true / false judgment module is configured to judge whether a current satellite signal contains a deceptive signal based on the 1-norm or the infinity-norm or the phase value of the autocorrelation matrix.

[0043] The present invention has at least the following beneficial effects:

[0044] The present invention not only enhances and clarifies the role of collaborative detection between multiple satellite signals and improves the accuracy of detection; at the same time, the detection results can be quantified and the threshold value can be easily set. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flowchart of a GNSS spoofing interference detection method based on signal direction vector autocorrelation according to an embodiment of the present invention is shown.

[0046] Figure 2 A structural diagram of a GNSS spoofing interference detection device based on signal direction vector autocorrelation according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention are further described in detail below with reference to the accompanying drawings and specific embodiments, but are not intended to limit the present invention. For the various steps described herein, if there is no necessity for a contextual relationship between each other, the order in which they are described as examples herein should not be regarded as limiting, and those skilled in the art should know that they can be adjusted in order as long as the logic between them is not destroyed, resulting in the inability to implement the entire process.

[0048] The embodiment of the present invention provides a GNSS deception interference detection method based on signal direction vector autocorrelation, such as Figure 1 FIG2 is a flow chart of a GNSS spoofing interference detection method based on signal direction vector autocorrelation. The GNSS spoofing interference detection method based on signal direction vector autocorrelation includes steps S10 to S40, which are described in detail below.

[0049] S10: storing and updating the direction vectors corresponding to the satellite signals and arranging them into a matrix.

[0050] In some embodiments, the direction vectors corresponding to the satellite signals are stored and updated, and arranged into a matrix, which is represented as:

[0051]

[0052] Where A represents the matrix, M is the dimension, which is the same as the number of array elements, and N is the number of satellite signals tracked. represents a complex set, and Represent the direction vectors of the first, second and Nth satellite signals respectively, They respectively represent the elevation angle and azimuth angle of the satellite signal reaching the receiving end.

[0053] S20: Multiply the matrix by the conjugate transpose of the matrix to obtain the autocorrelation matrix.

[0054] In some embodiments, the autocorrelation matrix is ​​obtained by multiplying the matrix by the conjugate transpose of the matrix using the following formula:

[0055] R AA =A H A

[0056] Where R AA represents the autocorrelation matrix, A H represents the conjugate transpose of a matrix, and A represents a matrix.

[0057] In some embodiments, the autocorrelation matrix is ​​a Hermitian matrix represented as:

[0058]

[0059] Where R AA The elements on the diagonal are equal to M; e represents the natural constant, m represents the array element number, and j represents the imaginary unit. represents the phase shift of the received signal of each array element corresponding to the i-th satellite; where i == 1, 2..., N.

[0060] In some embodiments, the detection matrix R AA The amplitude and phase characteristics of the elements are used to determine whether there is deceptive interference. Because when deceptive interference exists, different The phase difference between them is very small. Therefore, in terms of amplitude, the autocorrelation calculation process will show the coherent accumulation characteristics, R AA The modulus values ​​of each element in the equation tend to M; in terms of phase, R AA The phase angles corresponding to the elements in are close to 0. When there is no deception interference, the real satellite signal comes from a random direction, and the steering vector middle From [-π,π], it is roughly evenly distributed. AA Among the non-diagonal elements of , that is, i≠j, And it is triangularly randomly distributed. Therefore, in terms of amplitude, the coherent accumulation characteristics are significantly weakened during the autocorrelation calculation process, R AA Except for the diagonal elements whose modulus is equal to M, the modulus values ​​of other elements are obviously different and are all less than M. In terms of phase, since the real part of the matrix elements will randomly change positive or negative, R AA The phase angles corresponding to the elements in the equation will have two distribution results: close to 0 and ±π.

[0061] S30: Calculate the modulus and phase values ​​of the autocorrelation matrix elements, and calculate the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus values.

[0062] In this embodiment, the modulus and phase values ​​of all elements in the autocorrelation matrix are calculated. Based on the modulus, the 1-norm of the autocorrelation matrix || R AA ||1 or infinity norm||R AA || ∞ ,This process introduces the coordinated detection of all satellite signals.

[0063] S40: Determine whether the current satellite signal contains a deceptive signal based on the 1-norm or the infinity-norm or the phase value of the autocorrelation matrix.

[0064] In this embodiment, whether the current satellite signal contains a spoofing signal can be determined based on the 1-norm or infinity-norm of the autocorrelation matrix and / or based on the phase value of the autocorrelation matrix. Therefore, in a specific implementation, the following two modes can be formed for determination.

[0065] Mode 1: ||R AA ||1 or ||R AA || ∞ If it is less than the threshold detection threshold Γ=(M-1)N, it means it is a real signal; if it is greater than the threshold Γ=(M-1)N, it means there is a deceptive signal.

[0066] Mode 2: If the phase value approaches 0 and ±π, it indicates a real signal; if it only approaches 0, it indicates a spoofing signal.

[0067] The embodiment of the present invention also provides a GNSS deception interference detection device based on signal direction vector autocorrelation, such as Figure 2 As shown, the device includes:

[0068] The satellite signal direction vector buffer module 201 is configured to store and update the direction vectors corresponding to each satellite signal and arrange them into a matrix;

[0069] An autocorrelation matrix operation module 202 is configured to multiply the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix;

[0070] an amplitude and phase calculation module 203 configured to calculate the modulus and phase values ​​of the autocorrelation matrix elements, and calculate the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus;

[0071] The true / false judgment module 204 is configured to judge whether the current satellite signal contains a deceptive signal based on the 1-norm or the infinity-norm or the phase value of the autocorrelation matrix.

[0072] In some embodiments, the satellite signal direction vector cache module is further configured to store and update the direction vectors corresponding to each satellite signal and arrange them into a matrix, which is represented by:

[0073]

[0074] Where A represents the matrix, M is the dimension, which is the same as the number of array elements, and N is the number of satellite signals tracked. represents a complex set, and Represent the direction vectors of the first, second and Nth satellite signals respectively, They respectively represent the elevation angle and azimuth angle of the satellite signal reaching the receiving end.

[0075] In some embodiments, the autocorrelation matrix operation module is further configured to multiply the matrix by the conjugate transpose of the matrix using the following formula to obtain an autocorrelation matrix:

[0076] R AA =A H A

[0077] Where R AA represents the autocorrelation matrix, A H represents the conjugate transpose of a matrix, and A represents a matrix.

[0078] In some embodiments, the autocorrelation matrix is ​​represented as:

[0079]

[0080] In the formula, e represents the natural constant, m represents the array element number, j represents the imaginary unit, represents the phase shift of the received signal of each array element corresponding to the i-th satellite; where i == 1, 2..., N.

[0081] In some embodiments, the autocorrelation matrix operation module is further configured to:

[0082] The presence of deceptive interference is determined based on the amplitude and phase characteristics of the autocorrelation matrix elements. If deceptive interference exists, the amplitude and phase calculation module is instructed to calculate the modulus and phase values ​​of the autocorrelation matrix.

[0083] In some embodiments, the true or false judgment module is further configured to:

[0084] If the modulus of each element in the autocorrelation matrix approaches the dimension and / or the corresponding phase angle of each element in the autocorrelation matrix approaches 0, it is determined that deceptive interference exists.

[0085] In some embodiments, the autocorrelation matrix operation module is further configured to:

[0086] Determine a threshold value Γ = (M-1)N, where M is the dimension, which is the same as the number of array elements, and N is the number of tracked satellite signals;

[0087] If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​less than a threshold value, determining that the current satellite signal is a real signal;

[0088] If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​greater than or equal to a threshold value, it is determined that a deception signal exists in the current satellite signal.

[0089] In some embodiments, the true or false judgment module is further configured to:

[0090] If the phase value of the autocorrelation matrix element approaches 0 and ±π, it is determined that the current satellite signal is a real signal;

[0091] If the phase value of the autocorrelation matrix element only approaches 0, it is determined that a deception signal exists in the current satellite signal.

[0092] It should be noted that the structures of the various GNSS deception interference detection devices based on signal direction vector autocorrelation described in this embodiment belong to the same technical concept as the previously described GNSS deception interference detection method based on signal direction vector autocorrelation, and achieve the same beneficial effects through the same principles, which will not be repeated here.

[0093] Furthermore, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present invention having equivalent elements, modifications, omissions, combinations (e.g., schemes where various embodiments intersect), adaptations, or changes. The elements in the claims are to be interpreted broadly based on the language employed in the claims and are not limited to the examples described in this specification or during the prosecution of this application, which examples are to be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered as examples only, with the true scope and spirit being indicated by the following claims and the full scope of their equivalents.

[0094] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of their solutions) can be used in combination with each other. For example, those of ordinary skill in the art may use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features can be grouped together to simplify the present invention. This should not be interpreted as an intention that a feature of an invention that is not claimed for protection is necessary for any claim. On the contrary, the subject matter of the present invention may be less than all the features of the embodiments of a particular invention. Thus, the following claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim is independently a separate embodiment, and it is considered that these embodiments can be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the appended claims and the full scope of equivalents to which these claims are entitled.

Claims

1. A GNSS spoofing jamming detection method based on signal direction vector autocorrelation, characterized in that: The method comprises: The direction vectors corresponding to each satellite signal are stored and updated, and arranged into a matrix; Multiplying the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix; Calculating the modulus and phase values ​​of all elements of the autocorrelation matrix, and calculating the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus; Determining whether a current satellite signal contains a deceptive signal based on the 1-norm or the infinity-norm or the phase value of the autocorrelation matrix; After multiplying the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix, the method includes: determining whether deceptive interference exists based on the amplitude and phase characteristics of the autocorrelation matrix elements, and calculating the modulus and phase values ​​of the autocorrelation matrix elements if deceptive interference exists; Determining whether deceptive interference exists based on amplitude and phase characteristics of the autocorrelation matrix elements includes: If the modulus of each element in the autocorrelation matrix approaches the dimension and / or the corresponding phase angle of each element in the autocorrelation matrix approaches 0, it is determined that deceptive interference exists; Based on the 1-norm or infinity-norm of the autocorrelation matrix, the following method is used to determine whether the current satellite signal contains a spoofing signal: Determine a threshold value Γ = (M-1)N, where M is the dimension, which is the same as the number of array elements, and N is the number of tracked satellite signals; If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​less than a threshold value, determining that the current satellite signal is a real signal; If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​greater than or equal to a threshold value, it is determined that a deceptive signal exists in the current satellite signal; Based on the phase values ​​of the autocorrelation matrix elements, the following method is used to determine whether the current satellite signal contains a spoofing signal: If the phase value of the autocorrelation matrix element approaches 0 and ±π, it is determined that the current satellite signal is a real signal; If the phase value of the autocorrelation matrix element only approaches 0, it is determined that a deception signal exists in the current satellite signal.

2. The GNSS spoofing interference detection method based on signal direction vector autocorrelation according to claim 1 is characterized in that: The direction vectors corresponding to each satellite signal are stored and updated, and arranged into a matrix, which is represented as follows: Where A represents the matrix, M is the dimension, which is the same as the number of array elements, and N is the number of satellite signals tracked. represents a complex set, and Represent the direction vectors of the first, second and Nth satellite signals, θ, They respectively represent the elevation angle and azimuth angle of the satellite signal reaching the receiving end.

3. The GNSS spoofing interference detection method based on signal direction vector autocorrelation according to claim 2, characterized in that: The autocorrelation matrix is ​​obtained by multiplying the matrix by the conjugate transpose of the matrix using the following formula: R AA R AA =A H A Where R AA represents the autocorrelation matrix, A H represents the conjugate transpose of a matrix, and A represents a matrix.

4. The GNSS spoofing interference detection method based on signal direction vector autocorrelation according to claim 3 is characterized in that: The autocorrelation matrix is ​​expressed as: In the formula, e represents the natural constant, m represents the array element number, j represents the imaginary unit, represents the phase shift of the received signal of each array element corresponding to the i-th satellite; where i == 1, 2..., N.

5. A GNSS spoofing interference detection device based on signal direction vector autocorrelation, characterized in that: The device comprises: The satellite signal direction vector cache module is configured to store and update the direction vectors corresponding to each satellite signal and arrange them into a matrix; An autocorrelation matrix operation module is configured to multiply the matrix by the conjugate transpose of the matrix to obtain an autocorrelation matrix; an amplitude and phase calculation module, configured to calculate the modulus and phase values ​​of the autocorrelation matrix elements, and calculate the 1-norm or the infinity-norm of the autocorrelation matrix based on the modulus; a true / false judgment module configured to judge whether a current satellite signal contains a deceptive signal based on the 1-norm or the infinity-norm or the phase value of the autocorrelation matrix; The autocorrelation matrix operation module is further configured as follows: determining whether deceptive interference exists based on the amplitude and phase characteristics of the autocorrelation matrix elements, and, if deceptive interference exists, causing the amplitude and phase calculation module to calculate the modulus and phase values ​​of the autocorrelation matrix; The true / false judgment module is further configured to: If the modulus of each element in the autocorrelation matrix approaches the dimension and / or the corresponding phase angle of each element in the autocorrelation matrix approaches 0, it is determined that deceptive interference exists; The autocorrelation matrix operation module is further configured as follows: Determine a threshold value Γ = (M-1)N, where M is the dimension, which is the same as the number of array elements, and N is the number of tracked satellite signals; If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​less than a threshold value, determining that the current satellite signal is a real signal; If the 1-norm or the infinity-norm of the autocorrelation matrix is ​​greater than or equal to a threshold value, it is determined that a deceptive signal exists in the current satellite signal; The true / false judgment module is further configured to: If the phase value of the autocorrelation matrix element approaches 0 and ±π, it is determined that the current satellite signal is a real signal; If the phase value of the autocorrelation matrix element only approaches 0, it is determined that a deception signal exists in the current satellite signal.

6. A non-transitory computer-readable storage medium storing instructions, characterized in that: When the instructions are executed by a processor, the method according to any one of claims 1 to 4 is performed.

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