Radar anti-interference efficiency dynamic evaluation method based on expert experience matrix matching

Abstract

The invention belongs to the technical field of radars, and particularly discloses a radar anti-interference efficiency dynamic evaluation method based on expert experience matrix matching, which comprises the following steps: firstly, establishing an expert experience matrix library to formulate an equipment operation standard in a typical interference scene, and constructing an evaluation index system oriented to an operation process; then forming an equipment operation behavior description sequence and interference scene prior information according to collected radar equipment operation interface data and receiver processing data, performing staged multi-time matching on the equipment operation behavior description sequence and an expert experience matrix in a corresponding interference scene, and completing process evaluation by combining a matching result with an evaluation index system; experiments show that the method provided by the invention can effectively improve objectivity and accuracy of radar anti-interference efficiency evaluation under human-equipment combination, facilitates rapid positioning of operation problems, and can provide optimization guidance for equipment operation in a complex electromagnetic environment.

Description

Technical Field

[0001] The present invention belongs to the field of radar technology, and specifically discloses a method for dynamically evaluating radar anti-interference effectiveness based on expert experience matrix matching. Background Art

[0002] Evaluating radar anti-interference effectiveness with a human in the loop has always been a core issue in radar countermeasure testing and training in complex electromagnetic environments. With the integration of humans and equipment, the effectiveness of radar equipment is often significantly affected by human operation, resulting in individual differences. Based on the inherent capabilities of the equipment, equipment operation can influence the radar's air detection and tracking performance in complex electromagnetic environments by changing functional modes, resource scheduling, antenna beams, and other factors, and can also reflect the operator's tactical execution and coordinated countermeasure capabilities. Therefore, radar anti-interference effectiveness evaluation requires a comprehensive consideration of both the inherent capabilities of the equipment and its operation to reflect overall anti-interference effectiveness. A refined and objective evaluation method can not only improve the accuracy of radar anti-interference effectiveness evaluation, but also effectively identify equipment failures and operational issues, guiding the focus of subsequent countermeasure testing and training plans.

[0003] Based on the evaluation requirements during the equipment development and deployment phases, radar anti-interference effectiveness assessment generally uses two methods: semi-physical simulation and actual equipment. In the semi-physical simulation approach, by constructing a background signal environment, electromagnetic interference signal environment, and channel transmission environment, radar countermeasures are conducted under typical interference conditions using injection / anechoic chamber radiation. Signal data is collected, processed, and analyzed using simulators, acquisition equipment, and computers. Then, radar anti-interference effectiveness is evaluated using an indicator system. This approach is characterized by high repeatability of adversarial samples and good data collection completeness, but the realism of the adversarial environment is poor, the construction cost-effectiveness of the supporting system is relatively low, and the evaluation focuses on the inherent properties of the equipment, failing to fully consider the impact of the human-in-the-loop operational behavior sequence on system performance. In the actual confrontation mode, the radar equipment directly captures and tracks the aerial targets in a complex electromagnetic environment. The operator adopts multiple anti-interference measures within a certain period of time, and conducts radar anti-interference effectiveness evaluation by collecting parameters such as target detection probability, target tracking error, continuous tracking rate, true target recognition rate at the maximum target capture distance or a given distance. This method is characterized by a real confrontation environment, intuitive and highly reliable evaluation results, but focuses on static evaluation guided by confrontation results, and lacks process dynamic evaluations such as analysis of the rationality of the operator's equipment use. The evaluation results cannot effectively determine whether the confrontation problem is an equipment problem or an operation problem, and it is difficult to support the optimization of subsequent test training plans. Summary of the Invention

[0004] In order to solve the problems in the background technology, the present invention discloses a dynamic evaluation method for radar anti-interference effectiveness based on expert experience matrix matching, focusing on the rationality evaluation of equipment anti-interference operation under typical confrontation scenarios, highlighting the advantages of process dynamic evaluation in supporting radar anti-interference effectiveness and confrontation problem analysis, and adapting to future radar test training evaluation needs.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions:

[0006] The dynamic evaluation method of radar anti-interference effectiveness based on expert experience matrix matching mainly includes the establishment of an expert experience matrix library, the generation of radar equipment operation behavior description sequence, and the anti-interference operation evaluation based on multi-stage matching. The specific steps are as follows:

[0007] S1. Establishment of expert experience matrix library: Based on the type of interference suffered by the radar, signal strength and current radar working status, the type of interference includes noise interference and false target interference, signal strength refers to the interference energy entering the receiver, radar working status includes air search and tracking range and tracking error, and combined with combat operation mode, multiple typical interference scenarios are constructed, such as long-range noise support interference and false target self-defense interference. Then, the theoretical interference conditions that may occur in the signal data processing flow in the radar receiver under the interference scenario are analyzed, and combined with expert experience knowledge, an equipment operation standard matrix library in the confrontation process, namely, the expert experience matrix library, is constructed in advance to form an evaluation basis. Among them, the theoretical interference conditions are used to match the actual interference conditions as the basis for selection from the expert experience matrix library; a single equipment operation standard matrix, namely, the expert experience matrix, represents a certain interference type, interference intensity, and operation standard sequence under the radar working status;

[0008] S2. Radar equipment operation behavior description sequence generation: The radar equipment operation display and control screens within a certain time period, such as the PPI display interface, the command and control interface, and the number of target batches detected in the receiver, the interference energy amplitude, and the A-display screen are collected. Then, image processing algorithms are used to segment the display and control screens to complete the detection, tracking, and extraction of the operation behaviors of key selection and function selection, and form a radar equipment operation behavior description sequence with time stamps. The current radar interference situation is comprehensively judged using direct acquisition of equipment working data and image processing algorithms, forming radar interference status judgment information tightly coupled with the operation behavior description sequence. This information is used for segmenting the operation behavior description sequence and selecting the corresponding expert experience matrix.

[0009] S3. Anti-interference operation evaluation based on multi-stage matching: The equipment operation behavior description sequence is segmented according to the radar interference status judgment information and the radar working status changes, and the corresponding expert experience matrix is ​​selected for each segment. Then, multiple equipment operation behavior description sequence segments are matched with the corresponding expert experience matrix to complete multi-stage matching, establish an evaluation index system, and complete the quantitative evaluation of the rationality of anti-interference operation.

[0010] Furthermore, the radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching, in step S1, the expert experience matrix library contains equipment operation behavior standards under multiple radar interference scenarios, mainly including: radar interference scenario construction and expert experience matrix construction;

[0011] Radar jamming scenario construction: The current mainstream jamming styles include broadband noise, narrowband aiming frequency noise, dense false targets, distance / speed / integrated dragging, and slicing jamming. Jamming categories include long-range support, close-range support, and self-defense. Different jamming categories and jamming styles are combined, such as long-range support broadband noise jamming, close-range support narrowband aiming frequency noise jamming, and self-defense dense false target jamming. The jamming intensity is generally based on the jamming scenario type. The equivalent radiated power of the jammer and the radial distance between the jammer and the radar are taken as typical values, thus forming a relatively complete jamming scenario library, which is expressed as follows: And support update and expansion; i After the interference signal enters the radar receiver, it is subjected to theoretical analysis to form a theoretical interference analysis sequence, which is expressed as F i The theoretical interference analysis sequence mainly includes the interference distance range, interference spectrum range, the number of targets detected in a single wave gate, the change in interference signal strength, and specific analysis of different radar systems that may appear on the radar A display / P display. Among them, the interference distance range refers to the positional relationship between the interference signal and the echo signal, the interference spectrum range is the interference bandwidth coverage, and the number of targets detected in a single wave gate, including the number and interval of false targets. It is mainly used for the selection of equipment operation standard matrix in subsequent evaluation;

[0012] Expert experience matrix construction: According to I i 、F i The radar interference scenario and interference situation analysis is given, and the equipment operation standard is established by combining the interference countermeasure theory, equipment technical and tactical capability indicators and expert experience, which is expressed as H i =[h1,h2,...,h k ], multiple expert experience matrices can be constructed under multiple disturbance scenarios to form an expert experience matrix library, which is expressed as H:

[0013]

[0014] where h ij represents the jth equipment operation standard under the i-th radar interference scenario.

[0015] Furthermore, the radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching, the equipment operation behavior description sequence generation in step S2 mainly includes the construction of the operation behavior description sequence C and the radar interference state judgment information sequence J, J is used to match F i Match to select the expert experience matrix H corresponding to C i And by detecting the internal state changes of J, segment nodes are set on C to form multiple subsequences;

[0016] The construction of the operation behavior description sequence mainly includes: 1. During the confrontation process, the display and control interface of the radar equipment is directly collected through the equipment video interface or indirectly collected through external shooting, and it is disassembled into multiple frames of images and sorted to obtain the original data of the equipment operation behavior process; 2. The image frame is preprocessed, and the preprocessing mainly includes image angle correction, size / brightness adjustment, edge detection segmentation and noise filtering to improve the processing accuracy and efficiency of the image frame data; 3. The key selection, function selection and frequency switching operations in the image frame data are detected using traditional methods or deep learning-based methods. Generally, the position of the operation cursor is tracked for inference, and the current operation is detected by combining text recognition, image segmentation and other methods. Then, the operation of multiple adjacent image frame data is rearranged and inferred. The inference refers to the inference of the changes in the detection results of adjacent image frame data, and repeated clicks and redundant operations of incorrect operations are merged and eliminated; 4. The operation behavior description character c is formed. x With the corresponding timestamp t x And report; process all the original data within a certain period of time to obtain the operation behavior description sequence C={[c1,t1],[c2,t2],...,[c n ,t n ]};

[0017] Radar interference status judgment information sequence construction: Receiver processing data is collected, mainly including radar equipment display and control interface, receiver signal information processing data, and then the above data is parsed. According to the parsing results, the actual interference status of the current radar is judged, including the type and intensity of interference entering the receiver. The radar equipment display and control interface can be extracted by image processing-based methods. Combined with the directly collected receiver signal information processing data, the current target batch number, A display / P display interference phenomenon, and interference intensity information detected in the receiver are obtained to form a radar interference status judgment information sequence, which is expressed as

[0018] J={[j1,t s1 ,t e1 ],[j2,ts2 ,t e2 ],...,[j p ,t sp ,t ep ]} (2)

[0019] Where: j p Represents a relatively fixed radar interference state. The interference state of the entire judgment information sequence is classified using methods based on expert experience or deep learning to form multiple categories and obtain the state duration period, t sp , t ep Represents j p The start and end time of C are used to segment C into p segments, which can be expressed as:

[0020] C={[c1,c2,...c r ],[c r+1 ,c r+2 ,...c r+a ],...,[c r+a+b ,c r+a+b+1 ,...c n ]}={C1,C2,...,C p} (3)

[0021] Furthermore, in the radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching, the anti-interference operation evaluation based on multi-stage matching in step S3 is to combine the radar interference scenario I, the theoretical interference analysis result F, the expert experience matrix library H and the radar interference state judgment information sequence J to perform matching evaluation on the equipment operation behavior description sequence C, which can be expressed as:

[0022]

[0023] Where: P1(·) and P2(·) are matching functions and extraction functions, respectively, used to obtain the theoretical analysis results and expert experience matrix closest to the actual disturbance situation, L is the matched index, P3(·) is the matching function, used to achieve multi-stage matching of C and H, and obtain the matching result G, and distinguish multiple stages G = (g1, g2, ..., g p ).

[0024] Furthermore, in the radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching, the specific evaluation indicators in the matching process in step S3 include the first-level indicators: operation matching, operation timeliness and operation effectiveness, wherein the operation matching includes the second-level indicators operation matching index and operation integrity index, the operation timeliness includes the second-level indicators operation response index and operation coherence index, and the operation effectiveness includes the second-level indicator anti-interference effectiveness index;

[0025] Operation matching index, for equipment operation description sequence fragment C p Equipment Operation Standards The similarity calculation function is f1, which is generally calculated using the cross-correlation function. The larger the value, the better the operation matching and the more consistent with the theoretical operation standard.

[0026] Operate the full index to As a benchmark, C p The integrity of the correct operation is evaluated, and the integrity calculation function is f2;

[0027] Operational response index, corresponding to the disturbed state j p The starting time node t sp As the starting point, C p The time when the first correct operation is completed is the end point. The longer the time interval is, the worse the operation responsiveness is. The operation responsiveness calculation function is expressed as:

[0028]

[0029] Operational Coherence Index, combined C p The time interval between adjacent correct operations Extraction is performed, and then statistical averaging is performed. The larger the statistical average value, the worse the operation consistency. The operation consistency calculation function is expressed as:

[0030]

[0031] Immunity index, effective for The radar interference situation within the time period is analyzed. If the radar interference phenomenon is reduced and the target track / flight track appears, the equipment operation anti-interference is effective. The anti-interference effectiveness quantification calculation function is f5. If the target track / flight track appears, the value is 1, otherwise it is 0.

[0032] Combined with the index system, a quantitative evaluation of the rationality of the equipment's anti-interference operation during the confrontation process is completed. G is specifically expressed as:

[0033]

[0034] Where: F is the quantitative evaluation function, λ i 、f i Indicator weight coefficient and processing function respectively.

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] Aiming at the problem of evaluating the overall anti-interference effectiveness of radar under the combination of human and equipment, the present invention proposes a dynamic evaluation method based on expert experience matrix matching from the perspective of equipment anti-interference operation application evaluation. First, an expert experience matrix library is established to formulate equipment operation standards under typical interference scenarios, and an evaluation index system oriented to the operation process is constructed. Then, based on the collected radar equipment operation interface data and receiver processing data, a description sequence of equipment operation behavior and prior information of interference scenarios are formed. The equipment operation behavior description sequence is matched with the expert experience matrix under the corresponding interference scenario in multiple stages. The matching results are combined with the evaluation index system to complete the process evaluation. Experiments show that the proposed method can effectively improve the objectivity and accuracy of the anti-interference effectiveness evaluation of radar under the combination of human and equipment, help to quickly locate operation problems, and provide optimization guidance for equipment operation in complex electromagnetic environments.

[0037] This paper proposes a dynamic evaluation method based on expert experience matrix matching, focusing on the rationality assessment of equipment anti-interference operations in typical confrontation scenarios. It highlights the advantages of process-based dynamic evaluation in supporting radar anti-interference effectiveness and confrontation problem analysis. The feasibility and effectiveness of the proposed method are verified by experiments. By comprehensively utilizing multi-method data acquisition, image processing and analysis, and combining expert experience, a standard knowledge base and evaluation indicator system are established. This results in an evaluation process with good theoretical interpretability and high practical feasibility, which can improve the effectiveness of future radar system test and training. The following steps are taken: 1. The boundaries of radar anti-interference capability are grasped. By combining expert experience matrix iteration and theoretical analysis optimization and improvement, the actual radar anti-interference capability is continuously corrected using actual equipment confrontation results, providing effective support for commanders' decision-making. 2. The evaluation of test and training effectiveness is refined. By supplementing the equipment operation evaluation during the confrontation process, the evaluation of radar's confrontation effectiveness in complex electromagnetic environments is improved, helping to quickly locate confrontation problems. 3. The equipment operation strategy under confrontation is optimized. The anti-interference operation application method based on expert experience is segmented and quantified. This can support operators to optimize the equipment operation steps and sequence based on the evaluation results and formulate equipment operation strategies for different confrontation scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 Schematic diagram of the process dynamic evaluation framework of radar anti-interference effectiveness of the present invention;

[0040] Figure 2 This is a schematic diagram of the technical path for generating equipment operation behavior description sequences in the present invention;

[0041] Figure 3 It is a schematic diagram of the experimental scenario in the present invention;

[0042] Figure 4 This is a schematic diagram of radar display and control interface data collection and operation behavior analysis in the present invention;

[0043] Figure 5 It is a schematic diagram of the evaluation index results of each equipment in the disturbed scenario of the present invention;

[0044] Figure 6 It is the maximum detection distance of the radar to the target under different types of operations in the present invention. DETAILED DESCRIPTION

[0045] In order to better understand the present invention, the content of the present invention is further clearly set forth below in conjunction with the examples, but the protection content of the present invention is not limited to the following examples. In the following description, a large number of specific details are provided in order to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details.

[0046] Combined with attachment Figure 1-6 The present invention elaborates in detail the radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching, and the radar anti-interference effectiveness process dynamic evaluation framework is as follows Figure 1 As shown, the technical path for generating equipment operation behavior description sequence is as follows Figure 2 As shown in the figure, the proposed radar anti-interference effectiveness evaluation method is tested in combination with a tracking and guidance radar simulation system. By establishing a typical confrontation scenario, collecting data such as the radar system operation interface and working status, and combining the proposed evaluation index system to complete the multi-stage rationality quantitative evaluation of equipment operation.

[0047] 1. Radar Jamming Scenario Design

[0048] Design a typical radar interference scenario I, assuming the scenario is as follows Figure 3 As shown in the figure, in interference scenario 1, the penetrating fighter approaches the ground radar along route 1, and the electronic warfare aircraft performs a runway-type maneuver on the western extension of route 1 and releases broadband noise interference to the ground radar. When the penetrating fighter approaches midway, the electronic warfare aircraft switches the interference pattern to narrowband aiming frequency noise interference to continuously cover the fighter's penetration. In interference scenario 2, the penetrating fighter approaches the ground radar along route 2 and releases dense false target interference. When the penetrating fighter approaches midway, the fighter's self-defense interference pattern switches to slicing interference to continuously cover its own penetration. The specific parameter settings are shown in Table 1 below.

[0049] Table 1. Interference scenario parameter settings

[0050]

[0051]

[0052] 2. Disturbance Analysis and Expert Experience Matrix Construction

[0053] In a typical interference scenario, when the interference signal enters the radar receiver, the theoretical interference analysis results and the equipment operation standards (functional level) based on expert experience are shown in Table 2. Combined with Table 2, a theoretical interference analysis sequence F can be further formed. According to the characteristics of the tracking and guidance radar system, the equipment operation standards based on expert experience are converted into specific function buttons to form a corresponding expert experience matrix library H.

[0054] Table 2. Radar theoretical interference analysis results under interference scenarios and equipment operation standards based on expert experience (functional level)

[0055]

[0056]

[0057] 3. Equipment Operation Behavior and Disturbance Status Collection

[0058] In the designed interference scenario, the operator uses the tracking and guidance radar simulation system to carry out target search and tracking, and implements anti-interference operations during the confrontation process. The data acquisition equipment collects the system display and control interface, receives and processes data, generates the equipment operation behavior description sequence C and the radar interference status judgment information sequence J, and completes the segmentation of C by detecting J. The data acquisition and sequence generation diagram is shown as follows: Figure 4 As shown in Figure 3, each operation is time-labeled; the specific content generated is shown in Table 3.

[0059] Table 3. Radar interference status judgment information and actual equipment operation behavior collection content

[0060]

[0061] The weight coefficients in formula (7) are set to 0.25, 0.25, 0.2, 0.2, and 0.1 respectively, and the quantitative evaluation results G of the rationality of the equipment anti-interference operation during the confrontation process can be calculated, as shown in Table 4. Figure 5 As shown in the figure, in order to further reflect the difference in radar effectiveness caused by anti-interference operation, the difference in radar detection effectiveness under actual equipment operation and equipment operation based on expert experience is compared, and the maximum detection distance of the target in the same scene is quantified, as shown in the figure. Figure 6 shown.

[0062] Table 4. Evaluation results of equipment anti-interference operation rationality in typical interference scenarios

[0063]

[0064]

[0065] Combined with Table 3, Table 4, Figure 5 Analysis shows that in interference scenario 1, while the radar ultimately successfully counter-interferenced the jammer and achieved target re-tracking, issues such as slow effective operational response, inconsistent operation, and haphazard and inconsistent application of anti-interference measures led to poor operational consistency. This significantly reduced the radar's maximum target detection range, by an average of 26.79% compared to standard operation. Overall anti-interference performance was poor, with an average anti-interference score of 0.69. In interference scenario 2, operators, based on the results of previous assessments, implemented targeted improvements, focusing on optimizing equipment operation sequence, operational response, and consistency. For example, they prioritized passive tracking for direction finding of the jammer and prioritized anti-interference measures such as counter-reconnaissance and counter-spoofing in the presence of deception jamming. This provided effective guidance for jammer type identification and the application of anti-interference measures. The average anti-interference score was 0.80, a 16% improvement compared to interference scenario 1. The radar's maximum target detection range remained relatively close to the theoretical value under standard operation, decreasing by an average of 20.48% compared to standard operation, significantly improving overall anti-interference performance.

[0066] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limiting. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A dynamic evaluation method for radar anti-interference effectiveness based on expert experience matrix matching is characterized by: The steps include: S1. Establishing an expert experience matrix library: Based on the type of interference suffered by the radar, signal strength, and current radar operating status, multiple typical interference scenarios are constructed in combination with combat operation modes. Then, the theoretical interference conditions that may occur in the signal data processing flow within the radar receiver under the interference scenarios are analyzed. In combination with expert experience and knowledge, a standard matrix library for equipment operation in the confrontation process is constructed in advance, namely, the expert experience matrix library. The theoretical interference conditions are used to match the actual interference conditions as the basis for selection from the expert experience matrix library. A single equipment operation standard matrix represents a sequence of operation standards under a certain interference type, interference strength, and radar operating status. S2. Radar equipment operation behavior description sequence generation: The radar equipment operation display and control screen within a certain time period and the number of target batches detected in the receiver, the interference energy amplitude, and the A-display screen are collected. Then, image processing algorithms are used to segment the display and control screen to complete the detection, tracking, and extraction of the operation behavior of key selection and function selection, and form a radar equipment operation behavior description sequence with time stamps. The current radar interference situation is comprehensively judged using direct acquisition of equipment working data and image processing algorithms, forming radar interference status judgment information tightly coupled with the operation behavior description sequence. This information is used for segmenting the operation behavior description sequence and selecting the corresponding expert experience matrix. S3. Anti-interference operation evaluation based on multi-stage matching: The equipment operation behavior description sequence is segmented according to the radar interference status judgment information and the radar working status changes, and the corresponding expert experience matrix is ​​selected for each segment. Then, multiple equipment operation behavior description sequence segments are matched with the corresponding expert experience matrix to complete multi-stage matching, establish an evaluation index system, and complete the quantitative evaluation of the rationality of anti-interference operation.

2. The radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching according to claim 1 is characterized in that: The expert experience matrix library in step S1 contains equipment operation behavior standards under multiple radar interference scenarios, mainly including: radar interference scenario construction and expert experience matrix construction; Radar interference scenario construction: Different interference categories and interference patterns are combined. The interference intensity is generally based on the interference scenario type, and the equivalent radiated power of the interference source and the radial distance between the interference source and the radar are taken as typical values, thereby forming a relatively complete interference scenario library, which is expressed as And support update and expansion; i After the interference signal enters the radar receiver, it is subjected to theoretical analysis to form a theoretical interference analysis sequence, which is expressed as F i The theoretical interference analysis sequence mainly includes the interference distance range, interference spectrum range, the number of targets detected in a single wave gate, the change in interference signal strength, and the phenomena that may appear on the radar A display / P display. It is mainly used for the selection of equipment operation standard matrix in subsequent evaluation; Expert experience matrix construction: According to I i 、F i The radar interference scenario and interference situation analysis is given, and the equipment operation standard is established by combining the interference countermeasure theory, equipment technical and tactical capability indicators and expert experience, which is expressed as H i =[h1,h2,...,h k ], multiple expert experience matrices can be constructed under multiple disturbance scenarios to form an expert experience matrix library, which is expressed as H: where h ij represents the jth equipment operation standard under the i-th radar interference scenario.

3. The radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching according to claim 2 is characterized in that: The generation of equipment operation behavior description sequence in step S2 mainly includes the construction of operation behavior description sequence C and radar interference state judgment information sequence J. J is used to i Match to select the expert experience matrix H corresponding to C i And by detecting the internal state changes of J, segment nodes are set on C to form multiple subsequences; The construction of the operation behavior description sequence mainly includes:

1. directly or indirectly collecting the display and control interface of the radar equipment during the confrontation process, disassembling it into multiple frames of images and sorting them to obtain the original data of the equipment operation behavior process; 2. preprocessing the image frames, which mainly includes image angle correction, size / brightness adjustment, edge detection and segmentation, and noise filtering to improve the processing accuracy and efficiency of the image frame data; 3. using traditional methods or deep learning-based methods to detect the button selection, function selection, and frequency switching operations in the image frame data, and then rearrange and reason the operations of multiple adjacent image frame data, reason the changes in the detection results of adjacent image frame data, and merge and eliminate repeated clicks and redundant operations of erroneous operations; 4. forming the operation behavior description word c x With the corresponding timestamp t x And report; process all the original data within a certain period of time to obtain the operation behavior description sequence C={[c1,t1],[c2,t2],...,[c n ,t n ]}; Radar interference status judgment information sequence construction: Receiver processing data is collected, mainly including radar equipment display and control interface, receiver signal information processing data, and then the above data is parsed. According to the parsing results, the actual interference status of the current radar is judged, including the type and intensity of interference entering the receiver. The radar equipment display and control interface can be extracted by image processing-based methods. Combined with the directly collected receiver signal information processing data, the current target batch number, A display / P display interference phenomenon, and interference intensity information detected in the receiver are obtained to form a radar interference status judgment information sequence, which is expressed as J={[j1,t s1 ,t e1 ],[j2,t s2 ,t e2 ],...,[j p ,t sp ,t ep ]} (2) Where: j p Represents a relatively fixed radar interference state. The interference state of the entire judgment information sequence is classified using methods based on expert experience or deep learning to form multiple categories and obtain the state duration period, t sp , t ep Represents j p The start and end time of C are used to segment C into p segments, which can be expressed as: C={[c1,c2,...c r ],[c r+1 ,c r+2 ,...c r+a ],...,[c r+a+b ,c r+a+b+1 ,...c n ]}={C1,C2,...,C p }(3) 4. The radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching according to claim 3 is characterized in that: In step S3, the anti-interference operation evaluation based on multi-stage matching combines the radar interference scenario I, the theoretical interference analysis result F, the expert experience matrix library H, and the radar interference state judgment information sequence J to perform matching evaluation on the equipment operation behavior description sequence C, which can be expressed as: Where: P1(·) and P2(·) are matching functions and extraction functions, respectively, used to obtain the theoretical analysis results and expert experience matrix closest to the actual disturbance situation, L is the matched index, P3(·) is the matching function, used to achieve multi-stage matching of C and H, and obtain the matching result G, and distinguish multiple stages G = (g1, g2, ..., g p ).

5. The radar anti-interference effectiveness dynamic evaluation method based on expert experience matrix matching according to claim 4 is characterized in that: The specific evaluation indicators in the matching process in step S3 include the first-level indicators: operation matching, operation timeliness and operation effectiveness. Among them, operation matching includes the second-level indicators operation matching index and operation integrity index, operation timeliness includes the second-level indicators operation response index and operation coherence index, and operation effectiveness includes the second-level indicator anti-interference effectiveness index; Operation matching index, for equipment operation description sequence fragment C p Equipment Operation Standards The similarity calculation function is f1, which is generally calculated using the cross-correlation function. The larger the value, the better the operation matching and the more consistent with the theoretical operation standard. Operate the full index to As a benchmark, C p The integrity of the correct operation is evaluated, and the integrity calculation function is f2, the operation reaction index, corresponding to the disturbed state j p The starting time node t sp As the starting point, C p The time when the first correct operation is completed is the end point. The longer the time interval is, the worse the operation responsiveness is. The operation responsiveness calculation function is expressed as: Operational Coherence Index, combined C p The time interval between adjacent correct operations Extraction is performed, and then statistical averaging is performed. The larger the statistical average value, the worse the operation consistency. The operation consistency calculation function is expressed as: Immunity index, effective for The radar interference situation within the time period is analyzed. If the radar interference phenomenon is reduced and the target track / flight track appears, the equipment operation anti-interference is effective. The anti-interference effectiveness quantification calculation function is f5. If the target track / flight track appears, the value is 1, otherwise it is 0. Combined with the index system, a quantitative evaluation of the rationality of the equipment's anti-interference operation during the confrontation process is completed. G is specifically expressed as: Where: F is the quantitative evaluation function, λ i 、f i Indicator weight coefficient and processing function respectively.

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