Anti-deception interference method based on pattern comparison

Abstract

The application provides an anti-deception interference method based on figure contrast, which comprises the following steps: firstly, processing the received signals of radar stations to obtain local tracks of each radar; each radar station can obtain several tracks due to the interference of jammer; then, converting the position information of each track point into a unified coordinate system and performing time and space alignment; subsequently, performing slope subtraction and difference comparison on each track received by the radar, and the minimum value corresponding to the track is the real target track detected by each radar. The application can significantly reduce the calculation amount, does not need to consider the error covariance matrix, and the obtained target motion track is more accurate. In addition, the application adopts the method of selecting the minimum slope value to complete the anti-deception interference, does not need to calculate and select the threshold, eliminates the subjective factors in the threshold selection process, and has simpler principle, more convenient operation, and better anti-interference effect.

Description

Technical Field

[0001] This invention belongs to the field of radar imaging technology, specifically relating to an anti-deception interference method based on image comparison. Background Technology

[0002] There are many technologies in the field of radar imaging related to radar suppression of deceptive interference.

[0003] For example, patent application CN112666528A, entitled "An Interference Identification Method for Multi-Station Radar Systems Based on Convolutional Neural Networks," discloses a neural network-based method for resisting deceptive interference in radar systems. This method involves horizontally concatenating slow-time random complex envelope sequences to obtain a first two-dimensional data block; inputting this first two-dimensional training data block into a first interference identification network to obtain a first classification output; using gradient descent to minimize the loss function of the first interference identification network to obtain a second interference identification network; inputting the first two-dimensional data block into the second interference identification network; and obtaining a third interference identification network when the sum of errors in the second interference identification network is less than or equal to a threshold; finally, inputting the second two-dimensional data block into the third interference identification network to obtain the final classification output. This method improves the utilization rate of sampled data in the information processing of multi-station radar systems and achieves the identification of deceptive interference.

[0004] For example, patent application CN109633628A, entitled "Method for Combating RGPO Interference Based on Distributed Networked Radar Data Fusion," discloses a method for combating RGPO interference based on distributed networked radar data fusion. This method primarily addresses the problem of false tracks generated by RGPO interference, which cannot be overcome by existing technologies. The implementation scheme involves simulating a single target moving at a constant velocity in a plane to obtain the target's true track. Measurements from two radars in the network are then obtained from the target's true track. The measurements from each radar are filtered to obtain local tracks for each radar. An interference discrimination factor is calculated during the filtering process, and its discrimination threshold is determined. A fusion weight is then calculated. Based on the fusion weight, the two local tracks are fused at the fusion center to obtain a system track that approximates the target's true track. This effectively identifies and eliminates false tracks and can be used to effectively combat track deception interference in distributed networked radar systems.

[0005] In existing technologies, "a method for jamming identification in multi-station radar systems based on convolutional neural networks" classifies slow-time random complex envelope sequences to eliminate active false targets, thereby achieving the purpose of resisting deceptive jamming. The drawback of this method is that it heavily relies on the slow-time random complex envelope of the target, requiring significant resources for radar detection and information transmission.

[0006] The "Method for Anti-RGPO Interference Based on Distributed Networked Radar Data Fusion" is suitable for detecting targets moving at a constant speed in a straight line. However, in real-world scenarios, the magnitude and direction of the target's speed often change, and the trajectory is often curved. Furthermore, this method requires calculating the normalized distance of the information at each moment during the filtering process of each radar and calculating the interference factor discrimination threshold. The computational load is large, and whether the threshold is selected correctly will seriously affect the discrimination result and lead to a decrease in anti-interference performance. Summary of the Invention

[0007] To address the aforementioned problems in the existing technology, this invention provides an anti-spoofing interference method based on image comparison. The technical problem to be solved by this invention is achieved through the following technical solution:

[0008] This invention provides a method for resisting deception interference based on graphic comparison, comprising:

[0009] S100 transmits signals through multiple radar stations and receives received signals consisting of real targets and interference signals through the multiple radar stations;

[0010] S200, perform Kalman filtering on the received signal, and perform point correlation on the Kalman-filtered received signal to generate a motion track; the motion track includes the motion track of the real target and the motion track of the false target;

[0011] S300 transforms the motion trajectory to a polar coordinate system and aligns it in time and space; after alignment, it is transformed to a Cartesian coordinate system to obtain the motion trajectory in the Cartesian coordinate system.

[0012] S400, calculate the slope of each motion trajectory in the rectangular coordinate system, and compare the slopes of each motion trajectory by interpolation to obtain the sum of the slope interpolation between the motion trajectories;

[0013] S500 compares the sum of the slope interpolation values ​​between the motion trajectories and determines the trajectory corresponding to the minimum slope interpolation value as the motion trajectory of the real target.

[0014] Beneficial effects:

[0015] 1. This invention first processes the received signals from radar stations to obtain local tracks for each radar. Due to jamming, each radar station receives several tracks, one of which is the real target track, while the rest are false target tracks generated by the jammer. The position information of each point in the track is then converted to a unified coordinate system and aligned in time and space. Next, the slopes of the tracks received by this radar are subtracted from those received by other radars, and the differences are compared. Specifically, the differences in slopes between corresponding pairs of points are accumulated, and the minimum value is determined. This minimum value is then identified as the real target track detected by each radar. Compared to existing methods that calculate the cross-correlation coefficient of slow-time random complex envelope sequences of measurement information or calculate the Mahalanobis distance of radar measurements and compare it with a threshold, this method significantly reduces computational load, eliminates the need to consider the error covariance matrix, and yields more accurate target trajectories.

[0016] 2. This invention uses the method of selecting the minimum slope value to perform target trajectory similarity matching to complete the anti-deception interference. It does not require calculating and selecting a threshold, eliminates subjective factors in the threshold selection process, and has a simpler principle, is easier to operate, and has a better anti-interference effect.

[0017] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating an anti-spoofing interference method based on graphic comparison provided by the present invention.

[0019] Figure 2 The actual trajectory of the target movement;

[0020] Figure 3 The flight path map obtained by radar station 1 without anti-jamming processing;

[0021] Figure 4 The flight path map obtained by radar station 2 without anti-jamming processing;

[0022] Figure 5 This is a diagram showing the result of anti-jamming processing on the tracks obtained by radar station 1;

[0023] Figure 6 This is a diagram showing the results of anti-jamming processing on the tracks obtained by radar station 2;

[0024] Figure 7 The image shows a comparison between the final trajectory of radar station 1, the final trajectory of radar station 2, and the actual trajectory. Detailed Implementation

[0025] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0026] Radar is a device that uses radio waves to detect targets and determine their spatial location. In modern warfare, the confrontation between radar technology and counter-radar technology is a perennial issue. This involves understanding the detection characteristics of radar.

[0027] In modern complex electronic warfare, due to the low cost and high performance of digital radio frequency memory (DRFM), active deception jamming is now widely used in radar-targeting operations. However, this reduces the radar's ability to detect weak targets and seriously threatens the radar system's performance and survivability. Strong anti-jamming capabilities are essential for the survival of radar systems; therefore, researching countermeasures against range deception jamming has significant theoretical importance and broad military application prospects.

[0028] The purpose of this invention is to address the shortcomings of existing radar anti-spoofing and jamming technologies by proposing a multi-radar cooperative anti-jamming method based on curve similarity. Compared with existing anti-jamming technologies, this method eliminates the need to calculate selection thresholds, significantly reduces computational load, and is simpler in principle, easier to operate, and provides better anti-jamming performance.

[0029] The technical solution of the present invention will be described in detail below.

[0030] refer to Figure 1 This invention provides an anti-spoofing interference method based on graphic comparison, comprising:

[0031] S100 transmits signals through multiple radar stations and receives received signals consisting of real targets and interference signals through the multiple radar stations;

[0032] The transmitted signal is s(t), and the target echo signal is represented as...

[0033] s r (t) = s(t-t0);

[0034] in, R0 is the distance between the real target and the radar receiver, and c is the speed of light;

[0035] The range deception jamming signal can be represented as J(t), and the received signal at the radar station is:

[0036] S r (t)=s r (t)+J(t)+n(t);

[0037] Where n(t) represents a value with zero mean and variance of t. Gaussian noise.

[0038] S200, perform Kalman filtering on the received signal, and perform point correlation on the Kalman-filtered received signal to generate a motion track; the motion track includes the motion track of the real target and the motion track of the false target;

[0039] The received signal is subjected to Kalman filtering, point correlation, and track generation. Assuming the jammer interferes with two radar stations and generates a false target at a distance d before and after the real target, both radars can generate three tracks, one of which is the real target track and the rest are false target tracks.

[0040] The trajectory of the real target at 100 moments in a two-dimensional Cartesian coordinate system is as follows:

[0041]

[0042] The trajectory of the real target generated based on the received signal is as follows:

[0043] Z i,1 =[x i,1 ,y i,1 ;x i,2 ,y i,2 ;x i,3 ,y i,3 ...x i,100 ,y i,100 ]

[0044] Where i represents the radar site number, i = 1, 2 represents radar site 1 and radar site 2.

[0045] S300 transforms the motion trajectory to a polar coordinate system and aligns it in time and space; after alignment, it is transformed to a Cartesian coordinate system to obtain the motion trajectory in the Cartesian coordinate system.

[0046] S300 of the present invention includes:

[0047] S310, using the first conversion formula, converts the motion trajectory of the real target and the motion track of the false target to polar coordinates with the radar station as the pole;

[0048] S320 aligns the motion trajectories converted to polar scales in both time and space;

[0049] S330, using the second transformation formula, the aligned motion trajectory is transformed into a Cartesian coordinate system to obtain the motion trajectories of the real target and the false target in the Cartesian coordinate system.

[0050] Let the locations of the radar stations be [x] 1,0 ,y 1,0 ], [x 2,0 ,y2,0 As can be seen from the principle of deception jamming, the jammer generates false targets by intercepting and delaying the radar's transmitted signals. Therefore, the range deception false targets are distributed along the lines connecting the real targets and the radar stations. To calculate the measurements of the false targets, the real measurements are first converted to polar coordinates with radar stations 1 and 2 as poles. The first conversion formula is as follows:

[0051]

[0052]

[0053] The locations of the radar stations are [x] 1,0 ,y 1,0 ], [x 2,0 ,y 2,0 k = 1 to 100, representing the target's motion time;

[0054] The motion of the false target in polar coordinates:

[0055]

[0056]

[0057]

[0058]

[0059]

[0060]

[0061]

[0062]

[0063] ρ i,n,k d represents the angle information of the nth track of the i-th radar station at time k, where n = 1, 2, 3, and d is the deception distance;

[0064] The second conversion formula is:

[0065]

[0066] The trajectory in the Cartesian coordinate system is:

[0067] Z 1,1 =[x 1,1,1 ,y 1,1,1 ;x 1,1,2 ,y 1,1,2 ;x 1,1,3 ,y 1,1,3...x 1,1,100 ,y 1,1,100 ];

[0068] Z 1,2 =[x 1,2,1 ,y 1,2,1 ;x 1,2,2 ,y 1,2,2 ;x 1,2,3 ,y 1,2,3 ...x 1,2,100 ,y 1,2,100 ];

[0069] Z 1,3 =[x 1,3,1 ,y 1,3,1 ;x 1,3,2 ,y 1,3,2 ;x 1,3,3 ,y 1,3,3 ...x 1,3,100 ,y 1,3,100 ];

[0070] Z 2,1 =[x 2,1,1 ,y 2,1,1 ;x 2,1,2 ,y 2,1,2 ;x 2,1,3 ,y 2,1,3 ...x 2,1,100 ,y 2,1,100 ];

[0071] Z 2,2 =[x 2,2,1 ,y 2,2,1 ;x 2,2,2 ,y 2,2,2 ;x 2,2,3 ,y 2,2,3 ...x 2,2,100 ,y 2,2,100 ];

[0072] Z 2,3 =[x 2,3,1 ,y 2,3,1 ;x 2,3,2 ,y 2,3,2 ;x 2,3,3 ,y 2,3,3 ...x 2,3,100 ,y 2,3,100 ];

[0073] Among them, Z i,n This represents the nth motion track detected by the i-th radar station.

[0074] S400, calculate the slope of each motion trajectory in the rectangular coordinate system, and compare the slopes of each motion trajectory by interpolation to obtain the sum of the slope interpolation between the motion trajectories;

[0075] S400 of the present invention includes:

[0076] S410, calculate the slope of the trajectory in the rectangular coordinate system using the slope calculation formula;

[0077] The formula for calculating the slope is:

[0078]

[0079] Among them, K i,n,k This represents the slope of the k-th point of the n-th track detected by the i-th radar station;

[0080] S420: Using the slope interpolation formula, the slope of each motion trajectory is compared by slope interpolation to obtain the sum of the slope interpolation values ​​between the motion trajectories;

[0081] The slope interpolation formula is:

[0082]

[0083] Among them, Q m,n This represents the sum of the slope interpolation values ​​of each point of the m-th motion trajectory of the first radar station and the n-th motion trajectory of the second radar station, where m and n are both positive integers.

[0084] The above operations are performed on all tracks obtained from the radar station. Taking simulation conditions as an example, a total of 9 Qs can be obtained after the above operations, namely Q... 1,1 Q 1,2 Q 1,3 Q 2,1 Q 2,2 Q 2,3 Q 3,1 Q 3,2 Q 3,3 .

[0085] S500 compares the sum of the slope interpolation values ​​between the motion trajectories and determines the trajectory corresponding to the minimum slope interpolation value as the motion trajectory of the real target.

[0086] As the jammer intercepts radar signals and generates range deception signals, the positions of false targets are relatively dispersed in space. In contrast, the positions of real targets are more concentrated. Simulation results show that the trajectories of real targets detected by different radar stations almost overlap, while the trajectories of false targets differ significantly. This method considers the differences between the trajectories of real and false targets and uses curve similarity comparison in computer graphics to achieve anti-deception jamming. Specifically, it compares all Q values ​​obtained in step four, i.e., the sum of the inter-point slope interpolations corresponding to each trajectory, finds the minimum value, and considers the trajectory corresponding to the minimum value as the real target trajectory.

[0087] The anti-interference effect of the present invention will be illustrated by simulation below.

[0088] Combination Figures 2 to 7 , Figure 2 This represents the actual trajectory of the target. Figure 3 The track obtained by radar station 1 without anti-jamming processing is a real target with only one track. However, when three tracks are obtained, it is impossible to distinguish which track is the real target track. Figure 4 The track obtained by radar station 2 without anti-jamming processing is a real target with only one track. However, three tracks are obtained at this time, making it impossible to distinguish which track is the real target track. Figure 5 The results of anti-interference processing on the track obtained by radar station 1 show that after collaborative identification processing, the three tracks obtained by radar station 1 are reduced to one track, and the final track is the track of the real target. Figure 6 The results of anti-interference processing on the track obtained by radar station 2 show that after collaborative identification processing, the three tracks obtained by radar station 2 are reduced to one track, and the final track is the real target track. Figure 7 The image shows a comparison between the final trajectory of radar station 1 and radar station 2 and their actual trajectory. The comparison shows that both radar station 1 and radar station 2 successfully resisted range deception interference using this method, proving the effectiveness of this method.

[0089] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0090] Although this application has been described herein in conjunction with various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments by reviewing the accompanying drawings, the disclosure, and the appended claims in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality.

[0091] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A method for resisting deception interference based on graphic comparison, characterized in that, include: S100 transmits signals through multiple radar stations and receives received signals consisting of real targets and interference signals through the multiple radar stations; S200, perform Kalman filtering on the received signal, and perform point correlation on the Kalman-filtered received signal to generate a motion track; the motion track includes the motion track of the real target and the motion track of the false target; S300 converts the motion trajectory to polar coordinates and aligns it in time and space; After alignment, the motion trajectory in the Cartesian coordinate system is obtained. S400, calculate the slope of each motion trajectory in the rectangular coordinate system, and compare the slopes of each motion trajectory by interpolation to obtain the sum of the slope interpolation between the motion trajectories; S500 compares the sum of the slope interpolation values ​​between the motion trajectories and determines the trajectory corresponding to the minimum slope interpolation value as the motion trajectory of the real target.

2. The anti-spoofing interference method based on graphic comparison according to claim 1, characterized in that, The transmitted signal is s(t), and the target echo signal is represented as... s r (t) = s(t - t0); in, R0 is the distance between the real target and the radar receiver, and c is the speed of light; The range deception jamming signal can be represented as J(t), and the received signal at the radar station is: S r (t)=s r (t)+J(t)+n(t); Where n(t) represents a value with zero mean and variance of t. Gaussian noise.

3. The anti-spoofing interference method based on graphic comparison according to claim 2, characterized in that, The trajectory of the real target at 100 moments in a two-dimensional Cartesian coordinate system is as follows: The trajectory of the real target generated based on the received signal is as follows: Z i,1 =[x i,1 ,and i,1 ;x i,2 ,and i,2 ;x i,3 ,and i,3 ……x i,100 ,and i,100 ] Where i represents the radar site number.

4. The anti-spoofing interference method based on graphic comparison according to claim 3, characterized in that, The S300 includes: S310, using the first conversion formula, converts the motion trajectory of the real target and the motion track of the false target to polar coordinates with the radar station as the pole; S320 aligns the motion trajectories converted to polar scales in both time and space; S330, using the second transformation formula, the aligned motion trajectory is transformed into a Cartesian coordinate system to obtain the motion trajectories of the real target and the false target in the Cartesian coordinate system.

5. The anti-spoofing interference method based on graphic comparison according to claim 4, characterized in that, The first conversion formula in S310 is: The locations of the radar stations are [x] 1,0 ,y 1,0 ], [x 2,0 ,y 2,0 k = 1 to 100, representing the target's motion time; The motion of the false target in polar coordinates: ρ i,n,k Let d represent the angle information of the nth track of the i-th radar station at time k, where n = 1, 2, 3, and d is the deception distance.

6. The anti-spoofing interference method based on graphic comparison according to claim 5, characterized in that, The second conversion formula in S330 is: The trajectory in the Cartesian coordinate system is: Z 1,1 =[x 1,1,1 ,and 1,1,1 ;x 1,1,2 ,and 1,1,2 ;x 1,1,3 ,and 1,1,3 ……x 1,1,100 ,and 1,1,100 ]; Z 1,2 =[x 1,2,1 ,and 1,2,1 ;x 1,2,2 ,and 1,2,2 ;x 1,2,3 ,and 1,2,3 ……x 1,2,100 ,and 1,2,100 ]; Z 1,3 =[x 1,3,1 ,and 1,3,1 ;x 1,3,2 ,and 1,3,2 ;x 1,3,3 ,and 1,3,3 ……x 1,3,100 ,and 1,3,100 ]; Z 2,1 =[x 2,1,1 ,and 2,1,1 ;x 2,1,2 ,and 2,1,2 ;x 2,1,3 ,and 2,1,3 ……x 2,1,100 ,and 2,1,100 ]; Z 2,2 =[x 2,2,1 ,and 2,2,1 ;x 2,2,2 ,and 2,2,2 ;x 2,2,3 ,and 2,2,3 ……x 2,2,100 ,and 2,2,100 ]; Z 2,3 =[x 2,3,1 ,and 2,3,1 ;x 2,3,2 ,and 2,3,2 ;x 2,3,3 ,and 2,3,3 ……x 2,3,100 ,and 2,3,100 ]; Among them, Z i,n This represents the nth motion track detected by the i-th radar station.

7. The anti-spoofing interference method based on graphic comparison according to claim 6, characterized in that, The S400 includes: S410, calculate the slope of the trajectory in the rectangular coordinate system using the slope calculation formula; The formula for calculating the slope is: Among them, K i,n,k This represents the slope of the k-th point of the n-th track detected by the i-th radar station; S420: Using the slope interpolation formula, the slope of each motion trajectory is compared by slope interpolation to obtain the sum of the slope interpolation values ​​between the motion trajectories; The slope interpolation formula is: Among them, Q m,n This represents the sum of the slope interpolation values ​​of each point of the m-th motion trajectory of the first radar station and the n-th motion trajectory of the second radar station, where m and n are both positive integers.

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