A method for detection and suppression of a generative deception jamming based on a coprime array

Abstract

This invention discloses a generative deception interference detection and suppression method based on coprime arrays. After signal despreading, a grid-adaptive orthogonal matched pursuit algorithm is used for DOA estimation, and the sum of squared errors (SSE) of the DOA estimation results is used as the detection metric for deception interference. This is combined with a linearly constrained minimum variance algorithm to suppress generative deception interference. This invention maintains a high deception interference detection rate even in complex scenarios with severe multipath interference. It can detect and suppress generative deception interference before the induced correlation peak is stripped, adjust the array's main beam to align with the navigation signal, and improve the navigation signal's resistance to generative deception interference.

Description

Technical Field

[0001] This invention belongs to the field of navigation technology, specifically relating to a generative deception interference detection and suppression method based on coprime arrays. Background Technology

[0002] Satellite navigation systems are widely used in various critical infrastructures and public services. However, the satellite signal power received by users is typically only about -160 dBW, which is extremely low and susceptible to interference, leading to positioning failure. Among the many forms of interference, spoofing jamming is one of the main threats to satellite navigation security. Based on the generation principle of the jamming signal, spoofing jamming can be divided into two categories: generational and transponder-based. Generational spoofing jamming uses a dedicated signal generator to produce a spoofing signal with the same carrier frequency and modulation method as the real signal. However, it does not contain the correct navigation message, which can cause the receiver to be unable to correctly calculate the positioning information or output incorrect positioning results.

[0003] In recent years, antenna array technology has been increasingly used in the detection and suppression of deception interference. However, existing array anti-jamming methods are mostly designed for repeater-based deception scenarios, with limited effectiveness against generative interference. Compared to repeater-based interference, generative deception interference is more covert and deceptive, and more difficult to handle. Therefore, how to effectively detect and suppress generative deception interference has become a critical technical challenge that urgently needs to be overcome in the field of satellite navigation security.

[0004] Existing array anti-spoofing interference algorithms: Currently, commonly used anti-jamming algorithms based on antenna arrays mainly include Power Inversion (PI), Multiple Signal Classification (MUSIC), and beamforming combined anti-jamming algorithms. However, when facing generated deception jamming, because the power of the deception jamming is slightly higher than the navigation signal but much lower than the noise level, and the deception signal is highly correlated with the real signal, the MUSIC algorithm cannot accurately estimate the Direction of Arrival (DOA) information of the generated deception jamming, and PI cannot form nulls above the deception jamming to suppress it. Furthermore, in the early stages of the generated deception jamming, the power of the deception jamming is less than that of the navigation signal, and the performance of existing array anti-spoofing algorithms degrades more significantly, making it difficult to meet application requirements. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a generative deception interference detection and suppression method based on coprime arrays. After signal despreading, a Grid Adaptive Orthogonal Matching Pursuit (GA-OMP) algorithm is used for DOA estimation, and the sum of squared errors (SSE) of the DOA estimation results is used as the detection metric for deception interference. This is combined with a Linearly Constrained Minimum Variance (LCMV) algorithm to suppress generative deception interference. This invention maintains a high deception interference detection rate even in complex scenarios with severe multipath interference. It can detect and suppress generative deception interference before the induced correlation peak is stripped, adjust the array's main beam to align with the navigation signal, and improve the navigation signal's resistance to generative deception interference.

[0006] The technical solution adopted by this invention to solve its technical problem is as follows: Step 1: Establish a coprime array signal receiving model; Step 2: Despread the received signal; Step 3: Use the GA-OMP algorithm to estimate the DOA of the despread signal; Step 4: Repeat steps 2 to 3. After all satellite channel signals are estimated, perform generative spoofing interference detection and set the angle spoofing detection threshold. Step 5: Align the array's main beam using the LCMV algorithm. L A satellite signal is used to align the null trap with the deceptive signal.

[0007] Preferably, step 1 specifically comprises: A coprime array consists of two uniform linear subarrays with different numbers and spacings of elements; wherein, the spacing between elements in subarray 1 is... Nd The quantity is 2 M The spacing between the two elements of the subarray is Md The quantity is N , d The value is half the wavelength of the satellite signal; the two subarrays overlap only in their first element, and the synthesized coprime array has a total of 2 M + N -1 array element; Assume it exists L A real satellite signal and Q If a generative deception interference occurs, the coprime array will receive the signal. Represented as: (1) In the formula, and They represent innT Sampling time number l , The satellite signal and the q , The envelope data of a deceptive signal, and They represent the first l One direction is satellite signals and the q One direction is The steering vector of the deceptive signal, This represents spatial white noise that follows a Gaussian distribution. , They are represented as follows: (2) (3) In the formula, and express nT Sampling time number l The satellite signal and the q The power of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The navigation data code of the deceptive signal has a value of ±1; and express nT Sampling time number l The satellite signal and the q A pseudo-random code for a deceptive signal, with a value of ±1; Indicates the intermediate frequency (IF) of the receiver; and express nT Sampling time number l The satellite signal and the q Doppler shift of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The code phase offset of a deception signal; and express nT Sampling time number l The satellite signal and the q The initial phase of a deception signal; No. l Steering vector of each satellite signal and the q The guiding vector of a deception signal They represent: (4) (5) In the formula, Indicates the first i The distance between each physical array element and the reference array element. , λ Indicates the wavelength of the satellite signal. This represents transposition.

[0008] Preferably, step 2 specifically comprises: In the satellite star number k In the despreading channel, a local reference signal is first generated based on the Doppler frequency and code phase offset information captured by the receiver. : (6) in, , , , as well as They represent The navigation message, pseudo-random code, Doppler frequency shift, code phase offset, and phase; Then, for the number of snapshots... N s Received signal Despreading is performed; the despread signal... Represented as: (7).

[0009] Preferably, step 3 specifically comprises: Using a set of guide vectors U spaced 1° apart in the spatial domain as an overcomplete dictionary set, it is represented as: (8) Set threshold ,in ; This is the power threshold value. It represents the number of snapshots; the GA-OMP algorithm flow is expressed as follows: 1) Assume initial remaining quantity Support set as Number of iterations h =1; (9) 2) Find the remaining amount Let the maximum value of the atom's correlation with the atom in the overcomplete dictionary set U be the index value of that atom. , The first character of a complete dictionary setj The column, this step is represented as: (10) In the formula, It is the value of the variable when the function reaches its maximum value. express and The absolute value of the inner product; 3) In Generate angles with intervals of 0.1° around the corresponding angle, within the angle range. fine-grid dictionary set : (11) 4) Find the remaining amount With fine-grid dictionary set The maximum value of the atomic correlation value in the middle is set as follows: For fine-grid dictionary sets The j Column, assuming the index value of this atom is This step is represented as: (12) 5) Update the support set : (13) According to the support set The corresponding angle generates the guide vector group. As a support set:

[0010] 6) Solve for the current support set coefficient : (14) when The amplitudes are all greater than Continue with steps 7) through 8); when There are amplitudes less than the threshold When the algorithm process terminates, the output is... As an estimation result; 7) Update remaining quantity: (15) 8) Update the current iteration number Repeat steps 2) through 6 above. When the GA-OMP algorithm terminates, the output is... : (16) DOA information corresponding to the guide vector The satellite is numbered as s Within the despreading channel h -1 DOA estimation results for the signal.

[0011] Preferably, step 4 specifically comprises: Sort all DOA estimation results in descending order, each t Calculate the sum of squared errors for each angle. SSE This is used as a deceptive interference detection measure. m Deception interference detection quantity The calculation expression is: (17) In the formula, This indicates the DOA estimation results after being sorted in descending order. g Large angle value, Indicates the first m Within each angle window t The average of the DOA estimation results; All calculated deception interference detection quantities and In comparison, if deception interferes with the detection quantity Less than Then the first m From the angle window t Each DOA estimation result corresponds to one generative deception interference signal; the generative deception interference detection rule is expressed as: (18) In single-source deception interference scenarios, the average of all angle windows that meet the decision criteria is used as the generative deception interference. .

[0012] Preferably, step 5 specifically comprises: Based on the DOA estimation results, the constraint matrix C and constraint vector f are set as follows: (19) (20) In the formula, The angle of DOA estimation results from the GA-OMP algorithm after removing deceptive interference. After L The angle of attack with the greatest amplitude; The adaptive weights of the deception interference suppression array are expressed as follows: (twenty one) In the formula, Represents conjugate transpose; in The covariance matrix of the received data is represented as: (twenty two).

[0013] An electronic device includes: a processor and a memory; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the above-described generative deception interference detection and suppression method.

[0014] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described generative deception interference detection and suppression method.

[0015] A chip includes a processor for retrieving and running a computer program from a memory, causing a device on which the chip is mounted to perform the above-described generative spoofing interference detection and suppression method.

[0016] A computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the above-described generative spoofing interference detection and suppression method.

[0017] The beneficial effects of this invention are as follows: This invention provides a generative deception interference detection and suppression method based on coprime arrays. Compared with PI and methods that use MUSIC in conjunction with beamforming for deception interference detection and suppression, this invention can maintain a high deception interference detection rate even in complex scenarios with severe multipath interference. It can complete the detection and suppression of generative deception interference before the related peaks are induced and stripped by the generative deception interference, adjust the main beam of the array to align with the navigation signal, and improve the anti-generative deception interference performance of the navigation signal. Attached Figure Description

[0018] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is the physical array element distribution diagram of the coprime array used in this invention (2M=6, N=5).

[0019] Figure 3 This is the normalized DOA spatial spectrum obtained based on the GA-OMP algorithm in this embodiment of the invention.

[0020] Figure 4 This is a comparison between the LCMV algorithm in this embodiment of the invention and the array weight beam pattern obtained by PI. Detailed Implementation

[0021] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0022] To address the issues of low detection accuracy and poor suppression performance of current array anti-spoofing interference algorithms for generative spoofing interference, this invention proposes a generative spoofing interference detection and suppression method based on coprime arrays. This method can detect and suppress generative spoofing interference with low complexity and is applicable to multipath interference scenarios, thereby improving the satellite navigation system's ability to resist generative spoofing interference.

[0023] This invention proposes a generative spoofing interference detection and suppression algorithm based on coprime arrays. After signal despreading, the Grid Adaptive Orthogonal Matching Pursuit (GA-OMP) algorithm is used for DOA estimation, and the sum of squared errors (SSE) of the DOA estimation results is used as the spoofing interference detection quantity. The algorithm is combined with the Linear Constrained Minimum Variance (LCMV) algorithm to suppress generative spoofing interference.

[0024] The implementation steps of this invention are as follows: Step 1: Establish a coprime array signal receiving model. A coprime array consists of two uniform linear subarrays with different numbers and spacings of elements. The element spacing in the subarrays is... Nd The quantity is 2 M The spacing between the two elements of the subarray is Md The quantity is N , d The value is half the wavelength of the satellite signal. The two subarrays overlap only in their first element, and the resulting coprime array has a total of 2... M + N -1 array element. Assume there exists... L A real satellite signal and Q If a generative deception interference occurs, the coprime array will receive the signal. It can be represented as: (1) In the formula, and They represent in nT Sampling time number l ( ) satellite signal and the q ( The envelope data of a deceptive signal. and They represent the first l One direction is satellite signals and the q One direction is The steering vector of the deceptive signal, This represents spatial white noise that follows a Gaussian distribution. , They can be represented as: (2) (3) In the formula, and express nT Sampling time number l The satellite signal and the q The power of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The navigation data code of the deceptive signal has a value of ±1; and express nT Sampling time number l The satellite signal and the q A pseudo-random code for a deceptive signal, with a value of ±1; Indicates the intermediate frequency (IF) of the receiver; and express nT Sampling time number l The satellite signal and the q Doppler shift of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The code phase offset of a deception signal; and express nT Sampling time number l The satellite signal and the q The initial phase of a deception signal.

[0025] No. l Steering vector of each satellite signal and the q The guiding vector of a deception signal They represent: (4) (5) In the formula, Indicates the first i The distance between each physical array element and the reference array element. , λ Indicates the wavelength of the satellite signal. This represents transposition.

[0026] Step 2: Receive the signal Despreading is performed. (The satellite's asterisk is...) kIn the despreading channel, a local reference signal is first generated based on information such as the Doppler frequency and code phase offset captured by the receiver. : (6) in, , , , as well as They represent The navigation message, pseudo-random code, Doppler frequency shift, code phase offset, and phase.

[0027] Then, for the number of snapshots... N s Received signal Despreading is performed; the despread signal... Represented as: (7) Step 3: Despread the signal of this channel using the GA-OMP algorithm. DOA estimation is performed. A set of steering vectors U with a spatial spacing of 1° is used as the overcomplete dictionary set, represented as: (8) Set threshold ,in . This is the power threshold value. This refers to the number of snapshots. The GA-OMP algorithm flow can be represented as: 1) Assume initial remaining quantity Support set as Number of iterations h =1.

[0028] (9) 2) Find the remaining amount Let the maximum value of the atom's correlation with the atom in the overcomplete dictionary set U be the index value of that atom. , The first character of a complete dictionary set j This step can be represented as: (10) In the formula, It is the value of the variable when the function reaches its maximum value. express and The absolute value of the inner product.

[0029] 3) In Generate angles with intervals of 0.1° around the corresponding angle, within the angle range. fine-grid dictionary set : (11) 4) Find the remaining amount With fine-grid dictionary set The maximum value of the atomic correlation value in the middle is set as follows: For fine-grid dictionary sets The j Column, assuming the index value of this atom is This step can be represented as: (12) 5) Update the support set : (13) According to the support set The corresponding angle generates the guide vector group. As a support set:

[0030] 6) Solve for the current support set coefficient : (14) when The amplitudes are all greater than Continue with steps 7) through 8). There are amplitudes less than the threshold When the algorithm process terminates, the output is... As an estimate.

[0031] 7) Update remaining quantity: (15) 8) Update the current iteration number Repeat steps 2) to 6 above.

[0032] When the GA-OMP algorithm terminates, the output is... : (16) DOA information corresponding to the guide vector The satellite is numbered as s Within the despreading channel h -1 DOA estimation results for the signal.

[0033] Step 4: Repeat steps 2 and 3. After all satellite channel signals have been estimated, perform generative spoofing interference detection and set the angle spoofing detection threshold. Sort all DOA estimates in descending order, each... t Calculate the sum of squared errors for each angle. SSE This is used as a deceptive interference detection measure. m Deception interference detection quantity The calculation expression is: (17) In the formula, This indicates the DOA estimation results after being sorted in descending order. g Large angle value, Indicates the first m Within each angle window t The average of the DOA estimation results.

[0034] All calculated deception interference detection quantities and In comparison, if deception interferes with the detection quantity Less than Then the first m From the angle window t Each DOA estimation result corresponds to one generative spoofing interference signal. The generative spoofing interference detection rule can be expressed as: (18) In single-source deception interference scenarios, the average of all angle windows that meet the decision criteria is used as the generative deception interference. .

[0035] Step 5: Align the array's main beam using the LCMV algorithm. L The satellite signal is used to align the null trap with the spoofing signal. Based on the DOA estimation results, the constraint matrix C and constraint vector f are set as follows: (19) (20) In the formula, The angle of DOA estimation results from the GA-OMP algorithm after removing deceptive interference. After L The angle of attack with the greatest amplitude.

[0036] The adaptive weights of the deception interference suppression array can be expressed as: (twenty one) In the formula, This represents the conjugate transpose.

[0037] in The covariance matrix of the received data can be represented as: (twenty two) Example: This invention proposes a generative deception detection and suppression method based on coprime arrays, the implementation process of which is as follows: Figure 1 As shown. In this example, the center frequency of the carrier of the satellite signal and the generated spoofing interference is 1575.42MHz, which is then down-converted to... The sampling frequency is 4.092MHz, which means that each pseudo-random chip is sampled four times, and the number of snapshots is set to... This corresponds to receiving data in 1ms, with a signal-to-noise ratio (SNR) of -20dB, and the satellite signal power is set to... ,use M =3, N =5, a total of 2 M + N A coprime array with 10 elements (-1=1). The physical element distribution of the array is as follows. Figure 2 As shown. Exists in the spatial domain. L =Six satellite signals from different directions, with asterisks 3, 7, 12, 20, 23, and 32; angles of arrival are respectively , , , , , The code phase offsets are respectively , , , , , The Doppler frequency shifts are respectively , , , , , The initial phase is set to .exist There are three generative deception jammers, designated by asterisks 3, 7, 20, and 23, with an angle of arrival of [missing information]. Generative spoofing jamming produces code phase, Doppler shift, and initial phase that are completely identical to the corresponding satellite signal, and its power is also the same. Furthermore, multipath interference exists in the airspace with unknown numbers, satellite names, power attenuation, and directions of arrival. An angle spoofing detection threshold is set. ,set up The power threshold is 0.5. The specific steps of the generative spoofing interference detection process are as follows: (The value is -160dBw) Step 1: Establish a coprime array-based system nT Signal reception model at sampling time : (1) in, The navigation data code period is 20ms, which remains unchanged during sampling and is directly set to 1. The initial phase of both the deception signal and the navigation signal is set to 0. l A real signal and the q A deceptive signal It can be represented as: (2) (3) No. l Steering vector of each satellite signal and the q The guiding vector of a deception signal They represent: (4) (5) in, , which represents the signal wavelength. This represents transposition.

[0038] Step 2: Establish a local reference signal based on the Doppler frequency and code phase of the receiver's captured peak. Taking the despreading channel with asterisk 3 as an example, its local reference signal can be expressed as: (6) The received signal after despreading in channel 3 Represented as: (7) Step 3: According to Quick shot number Power threshold P Calculate threshold : (8) Let the angle range of the fine grid dictionary be... The GA-OMP algorithm is used to... DOA estimation is performed. A set of steering vectors U spaced 1° apart in the spatial domain is used as the overcomplete dictionary set in the spatial domain, which can be represented as: (9) Entering the GA-OMP algorithm flow: 1) Initialize the remaining amount , support set is Number of iterations h =1.

[0039] (10) 2) Find the remaining amount Let the maximum value of the atom's correlation with the atom in the overcomplete dictionary set U be the index value of that atom. ,set up The first complete dictionary set U j This step can be represented as: (11) 3) The solution is obtained Generate a fine-mesh dictionary set in its vicinity. , Its expression is (12) 4) Find the remaining amount With fine-grid dictionary set The maximum value of the atomic correlation value, let the index of that atom be . ,set up For fine-grid dictionary sets The j This step can be represented as: (36) 5) Find Update the index set: (13) 6) Update the support set based on the index set. Then, the coefficients under the current support set are solved using the least squares method. : (14) This value is greater than the threshold. Continue iterating the algorithm.

[0040] 7) Update remaining quantity : (15) 8) Update the current iteration number Repeat steps (2) to (6) above.

[0041] The GA-OMP process obtained respectively , ,in There are below the threshold The amount, retain The corresponding DOA estimation results. The despread signal with asterisk 3 contains two signals, and its DOA estimation results are [15°, -39.9°].

[0042] Repeat steps two and three until the despread signals with asterisks 3, 7, 12, 20, 23, and 32 have all completed DOA estimation. The resulting DOA normalized spatial spectrum is shown below. Figure 3 As shown.

[0043] Step 4: Detect generative deception interference, sort the DOA estimation results, and assign a ranking to each... t =Calculate from 3 angles SSE There are two in total. SSE The values ​​below the angle threshold of 0.5 are 0.0467 and 0.14 respectively. Their corresponding angle windows are [15.1°, 15.2°, 15.4°] and [14.7°, 15.1°, 15.2°]. Taking the average value of 15.1° as the direction of the deception interference, the DOA estimation error for the deception interference is 0.1°.

[0044] Step 5: Use the LCMV algorithm to align the array's main beam with the real satellite signal and the nulls with the spoofed signal. The estimated DOAs of the real signals are -39.9°, 49.8°, 5.2°, 37°, -25.2°, and 28°, with estimation errors of 0.1°, 0.2°, 0.2°, 0°, 0.2°, and 0°, respectively. Set the constraint matrix and constraint vectors as follows: (16) (17) Covariance matrix of received signal Represented as: (18) The array weights for spoofing interference suppression and navigation signal reception can be expressed as: (19) The array weighted beam pattern obtained by the LCMV algorithm is compared with the array weighted beam pattern obtained by directly applying the PI algorithm in the same scenario, as shown in Figure 4. It can be seen that the PI algorithm cannot effectively suppress generative spoofing interference, and even forms nulls above the real signal. In contrast, the proposed technique, after estimating the DOA of the real and spoofing signals, can align the array main lobe with the real signal and form nulls above the spoofing interference.

Claims

1. A generative deception interference detection and suppression method based on coprime arrays, characterized in that, Includes the following steps: Step 1: Establish a coprime array signal receiving model; Step 2: Despread the received signal; Step 3: Use the GA-OMP algorithm to estimate the DOA of the despread signal; Step 4: Repeat steps 2 to 3. After all satellite channel signals are estimated, perform generative spoofing interference detection and set the angle spoofing detection threshold. Step 5: Align the array's main beam using the LCMV algorithm. L A satellite signal is used to align the null trap with the deceptive signal.

2. The generative deception interference detection and suppression method based on coprime arrays according to claim 1, characterized in that, Step 1 specifically involves: A coprime array consists of two uniform linear subarrays with different numbers and spacings of elements; wherein, the spacing between elements in subarray 1 is... Nd The quantity is 2 M The spacing between the two elements of the subarray is Md The quantity is N , d The value is half the wavelength of the satellite signal; the two subarrays overlap only in their first element, and the synthesized coprime array has a total of 2 M+N -1 array element; Assume it exists L A real satellite signal and Q If a generative deception interference occurs, the coprime array will receive the signal. Represented as: (1) In the formula, and They represent in nT Sampling time number l , The satellite signal and the q , The envelope data of a deceptive signal, and They represent the first l One direction is satellite signals and the q One direction is The steering vector of the deceptive signal, This represents spatial white noise that follows a Gaussian distribution. , They are represented as follows: (2) (3) In the formula, and express nT Sampling time number l The satellite signal and the q The power of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The navigation data code of the deceptive signal has a value of ±1; and express nT Sampling time number l The satellite signal and the q A pseudo-random code for a deceptive signal, with a value of ±1; Indicates the intermediate frequency (IF) of the receiver; and express nT Sampling time number l The satellite signal and the q Doppler frequency shift of a deceptive signal; and express nT Sampling time number l The satellite signal and the q The code phase offset of a deception signal; and express nT Sampling time number l The satellite signal and the q The initial phase of a deception signal; No. l Steering vector of each satellite signal and the q The guiding vector of a deception signal They represent: (4) (5) In the formula, Indicates the first i The distance between each physical array element and the reference array element. , λ Indicates the wavelength of the satellite signal. This represents transposition.

3. The generative deception interference detection and suppression method based on coprime arrays according to claim 2, characterized in that, Step 2 specifically involves: In the satellite star number k In the despreading channel, a local reference signal is first generated based on the Doppler frequency and code phase offset information captured by the receiver. : (6) in, , , , as well as They represent The navigation message, pseudo-random code, Doppler frequency shift, code phase offset, and phase; Then, for the number of snapshots... N s Received signal Despreading is performed; the despread signal... Represented as: (7)。 4. The generative deception interference detection and suppression method based on coprime arrays according to claim 3, characterized in that, Step 3 specifically involves: Using a set of guide vectors U spaced 1° apart in the spatial domain as an overcomplete dictionary set, it is represented as: (8) Set threshold ,in ; This is the power threshold value. It represents the number of snapshots; the GA-OMP algorithm flow is expressed as follows: 1) Assume initial remaining quantity Support set as Number of iterations h =1; (9) 2) Find the remaining amount Let the maximum value of the atom's correlation with the atom in the overcomplete dictionary set U be the index value of that atom. , The first character of a complete dictionary set j The column, this step is represented as: (10) In the formula, It is the value of the variable when the function reaches its maximum value. express and The absolute value of the inner product; 3) In Generate angles with intervals of 0.1° around the corresponding angle, within the angle range. fine-grid dictionary set : (11) 4) Find the remaining amount With fine-grid dictionary set The maximum value of the atomic correlation value in the middle, let it be For fine-grid dictionary sets The j Column, assuming the index value of this atom is This step is represented as: (12) 5) Update the support set : (13) According to the support set The corresponding angle generates the guide vector group. As a support set: 6) Solve for the current support set coefficient : (14) when The amplitudes are all greater than Continue with steps 7) through 8); when There are amplitudes less than the threshold When the algorithm process terminates, the output is... As an estimate; 7) Update remaining quantity: (15) 8) Update the current iteration number Repeat steps 2) through 6 above. When the GA-OMP algorithm terminates, the output is... : (16) DOA information corresponding to the guide vector The satellite is numbered as s Within the despreading channel h -1 DOA estimation results for the signal.

5. The generative deception interference detection and suppression method based on coprime arrays according to claim 4, characterized in that, Step 4 specifically involves: Sort all DOA estimation results in descending order, each t Calculate the sum of squared errors for each angle. SSE This is used as a deception and interference detection measure. m Deception interference detection quantity The calculation expression is: (17) In the formula, This indicates the DOA estimation results after being sorted in descending order. g Large angle value, Indicates the first m Within each angle window t The average of the DOA estimation results; All calculated deception interference detection quantities and In comparison, if deception interferes with the detection quantity Less than Then the first m From the window at various angles t Each DOA estimation result corresponds to one generative deception interference signal; the generative deception interference detection rule is expressed as: (18) In single-source deception interference scenarios, the average of all angle windows that meet the decision criteria is used as the generative deception interference. .

6. The generative deception interference detection and suppression method based on coprime arrays according to claim 5, characterized in that, Step 5 specifically involves: Based on the DOA estimation results, the constraint matrix C and constraint vector f are set as follows: (19) (20) In the formula, The angle of DOA estimation results from the GA-OMP algorithm after removing deceptive interference. After L The angle of attack with the greatest amplitude; The adaptive weights of the deception interference suppression array are expressed as follows: (21) In the formula, Represents conjugate transpose; in The covariance matrix of the received data is represented as: (22)。 7. An electronic device, characterized in that, include: Processor and memory; The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 6.

9. A chip, characterized in that, include: A processor for retrieving and running a computer program from memory, causing a device on which the chip is mounted to perform the method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer storage medium storing a computer program, the computer program including instructions executable by at least one processor, which, when executed by the at least one processor, implement the method as described in any one of claims 1 to 6.

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