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CN-121980744-A - Anti-interference decision-making method of electronic target simulation equipment based on hierarchical strategy library

CN121980744ACN 121980744 ACN121980744 ACN 121980744ACN-121980744-A

Abstract

The application relates to the technical field of electronic countermeasure simulation, in particular to an anti-interference decision method of electronic target simulation equipment based on a hierarchical strategy library, which comprises the following steps of constructing the hierarchical strategy library; the hierarchical strategy library comprises a base layer strategy library, a scene layer strategy library and a dynamic strategy library, an interference situation map is generated based on received interference signals, a multi-level strategy screening mechanism is established, anti-interference candidate strategies are obtained from the hierarchical strategy library based on the interference situation map, methods matched by strategy libraries of different levels are different, a comprehensive efficiency evaluation model is established, an optimal anti-interference strategy is obtained from all anti-interference candidate strategies through the comprehensive efficiency evaluation model, the optimal anti-interference strategy is executed, the optimal anti-interference strategy is issued to a signal processing unit through a standard interface, and meanwhile, the execution state is monitored and execution effect data are recorded. The method can solve the technical problems of response lag and poor adaptability of the traditional electronic target simulation equipment anti-interference decision.

Inventors

  • REN DAN
  • Tian Manyu
  • FENG YU

Assignees

  • 西安长远电子工程有限责任公司

Dates

Publication Date
20260505
Application Date
20251209

Claims (10)

  1. 1. An anti-interference decision-making method of electronic target simulation equipment based on a hierarchical policy library is characterized by comprising the following steps: constructing a hierarchical policy library, wherein the hierarchical policy library comprises a base layer policy library, a scene layer policy library and a dynamic policy library; generating an interference situation map based on the received interference signals, wherein the interference situation map comprises characteristic vectors and situation grade assessment; establishing a multi-level strategy screening mechanism, and acquiring anti-interference candidate strategies from a hierarchical strategy library based on an interference situation map by the multi-level strategy screening mechanism, wherein the methods matched by strategy libraries of different levels are different; Constructing a comprehensive efficiency evaluation model, and obtaining an optimal anti-interference strategy from each anti-interference candidate strategy through the comprehensive efficiency evaluation model; Executing the optimal anti-interference strategy, issuing the optimal anti-interference strategy to the signal processing unit through the standard interface, and simultaneously monitoring the execution state and recording the execution effect data.
  2. 2. The method of claim 1, wherein the building a hierarchical policy repository comprises: A base layer policy library is constructed by adopting a relational database, wherein the base layer policy library stores single-parameter anti-interference policies of signal dimension characteristics, each policy comprises a policy ID, an application condition, a parameter adjustment range and an expected effect evaluation index, and a rule engine is adopted to realize quick matching; a scene layer strategy library is constructed based on a distance classification algorithm, wherein the scene layer strategy library stores a multi-dimensional combination strategy for a typical interference scene, extracts multi-dimensional feature vectors based on historical interference data, establishes a mapping relation between scene features and anti-interference strategy combinations, and classifies the scenes through feature similarity; The method comprises the steps of storing historical interference events and execution results of strategies corresponding to the historical interference events by using a time sequence database to construct a dynamic strategy library, wherein the dynamic layer strategy library stores historical interference event data by using the time sequence database, each record comprises a time stamp, interference feature vectors, an adopted strategy, an execution result and efficiency evaluation, and supports strategy retrieval based on similarity matching.
  3. 3. The method of claim 1, wherein generating an interference situation map based on the received interference signal comprises: Extracting the multi-dimensional characteristics of the interference signals to obtain characteristic parameters of the interference signals, wherein the characteristic parameters comprise intensity characteristic parameters, style characteristic parameters, time-frequency domain characteristic parameters and space characteristic parameters; The characteristic parameters of the interference signals are normalized and fused to convert the characteristic parameters into standard dimensions, so that a unified characteristic vector is formed; and calculating interference situation level assessment by a fuzzy comprehensive evaluation algorithm based on the unified feature vector so as to generate an interference situation map.
  4. 4. A method according to claim 3, wherein the normalization process uses a Min-Max normalization algorithm to map each characteristic parameter to a [0,1] interval, and the calculation formula is as follows: ; Wherein, the The normalized characteristic value is represented by a characteristic value, The characteristic parameter is represented by a characteristic parameter, Representing the minimum value of a parameter feature, i.e. the lower limit value at which the feature parameter may occur within the scope of the current system definition or calibration, Representing the maximum value of the parameter characteristic, namely the possible upper limit value of the characteristic parameter in the range of the current system definition or calibration; The feature fusion adopts a weighted fusion algorithm, and the calculation formula is as follows: ; Wherein, the The weights of the various characteristic parameters are represented, Representing the normalized eigenvalue; calculating interference situation score through fuzzy comprehensive evaluation algorithm Is expressed by the following formula: ; Wherein, the And the feature membership of the feature parameters is represented.
  5. 5. The method of claim 1, wherein the multi-level policy screening mechanism comprises: calculating probability distribution of each characteristic parameter, further obtaining a comprehensive interference entropy value and determining an optimal strategy library level, wherein the comprehensive interference entropy value represents complexity of the whole interference environment; In a base layer strategy library, a rule matching algorithm is adopted to carry out rapid matching of single-dimensional interference characteristics, and a base anti-interference candidate strategy is output; In a scene layer strategy library, realizing multi-dimensional feature similarity matching by calculating Euclidean distance, and applying a K nearest neighbor algorithm to classify scenes and outputting a scene combination candidate strategy; And setting effective cases of similarity threshold screening by adopting a compound similarity measurement method based on candidate strategies successfully handled by historical data similarity retrieval in a dynamic layer strategy library, wherein the compound similarity measurement method comprises feature space similarity, interference intensity similarity and scene context similarity.
  6. 6. The method of claim 5, wherein the integrated interference entropy value The calculation formula of (2) is as follows: ; Wherein, the The dimensions of the respective characteristic parameters are represented, Representing the statistical probability duty ratio of each characteristic parameter in the total interference characteristic; Optimal policy repository hierarchy The calculation formula of (2) is as follows: ; Wherein, the A maximum interference entropy value preset for the system; In the dynamic layer policy library, the effective cases of similarity threshold screening are set by adopting a composite similarity measurement method based on the history data similarity retrieval success coping policy, and the method comprises the following steps: the feature space similarity adopts cosine similarity The calculation formula of (2) is as follows: ; Wherein, the Representing the current set of interference feature vectors, Representing a set of historical interference feature vectors; Interference intensity similarity The calculation formula of (2) is as follows: ; Wherein, the Representing intensity similarity; representing the current interference strength normalized value, Representing a normalized value of the interference intensity of the historical scene; Scene context similarity The calculation formula of (2) is as follows: ; Wherein, the Indicating that the task type matches the weight, The degree of matching of the task types is indicated, Indicating that the device state matches the weight, Representing the device state matching degree, an 。
  7. 7. The method of claim 1, wherein the constructing the comprehensive performance evaluation model and obtaining the optimal anti-interference strategy from each anti-interference candidate strategy through the comprehensive performance evaluation model comprises: Acquiring an evaluation index system, wherein the evaluation index system comprises policy execution time consumption, system resource occupancy rate, historical success rate and scene matching degree; based on the evaluation index system, calculating the comprehensive efficacy score by adopting a weighted summation method, wherein the comprehensive efficacy score is specifically expressed by the following formula: ; Wherein, the Representing interference-free candidate strategies Is a comprehensive efficacy score of (2); respectively representing index weight coefficients; representing interference-free candidate strategies Is a normalized execution time-consuming score of (c), Representing interference-free candidate strategies Is a normalized resource occupancy score of (1), Representing interference-free candidate strategies Is a normalized historical success rate score of (c), Representing interference-free candidate strategies Is matched with the normalized scene of the score; And obtaining an optimal anti-interference strategy from each anti-interference candidate strategy based on the comprehensive efficiency scores.
  8. 8. The method according to any one of claims 1 to 7, further comprising: Based on the execution effect data, adopting an intelligent learning algorithm to continuously optimize the layering strategy library, wherein the optimizing time comprises periodic optimization, event-driven optimization and performance early warning optimization.
  9. 9. An electronic device comprising a processor and a memory, the memory having stored therein instructions executable by the processor, the processor configured to, when executed, cause the electronic device to implement the hierarchical policy library-based electronic target simulation device tamper resistant decision method of any one of claims 1 to 8.
  10. 10. A computer readable storage medium storing a computer program, wherein the computer program, when executed by a processor, is capable of implementing the hierarchical policy library-based anti-interference decision method for an electronic target simulation device according to any one of claims 1 to 8.

Description

Anti-interference decision-making method of electronic target simulation equipment based on hierarchical strategy library Technical Field The embodiment of the application relates to the technical field of electronic countermeasure simulation, in particular to an anti-interference decision-making method of electronic target simulation equipment based on a hierarchical strategy library. Background Under the background of the current training requirements of electronic combat practice tests, an electronic target simulator is used as a blue army to simulate and play a strong opponent to fight, signal parameters are required to be flexibly changed according to the characteristics of electronic combat equipment, threat target information of a red army is generated, and the effect of dynamic game is achieved, but due to the reasons of cost, expansibility and the like, the electronic target simulator cannot sense interference and autonomously resist interference like real equipment. The existing electronic target anti-interference decision is mostly completed through a static strategy library, dynamic load interference cannot be handled, the decision has hysteresis, the strategy library needs to be updated periodically, and timeliness, adaptability and effectiveness cannot be guaranteed. Disclosure of Invention In view of the above, the embodiment of the application provides an anti-interference decision method of electronic target simulation equipment based on a hierarchical policy library, which aims to solve the technical problems of response lag and poor adaptability of the traditional anti-interference decision of the electronic target simulation equipment, and remarkably improves the intelligent level and instantaneity of the anti-interference decision of the electronic target simulation equipment through a hierarchical collaborative decision and closed loop optimization mechanism. In order to achieve the above objective, an embodiment of the present application provides an anti-interference decision method for an electronic target simulation device based on a hierarchical policy library, where the method includes: constructing a hierarchical policy library, wherein the hierarchical policy library comprises a base layer policy library, a scene layer policy library and a dynamic policy library; generating an interference situation map based on the received interference signals, wherein the interference situation map comprises characteristic vectors and situation grade assessment; establishing a multi-level strategy screening mechanism, and acquiring anti-interference candidate strategies from a hierarchical strategy library based on an interference situation map by the multi-level strategy screening mechanism, wherein the methods matched by strategy libraries of different levels are different; Constructing a comprehensive efficiency evaluation model, and obtaining an optimal anti-interference strategy from each anti-interference candidate strategy through the comprehensive efficiency evaluation model; Executing the optimal anti-interference strategy, issuing the optimal anti-interference strategy to the signal processing unit through the standard interface, and simultaneously monitoring the execution state and recording the execution effect data. In order to achieve the above objective, an embodiment of the present application further provides an anti-interference decision device for an electronic target simulation device based on a hierarchical policy library, where the device includes: The system comprises a construction module, a dynamic policy library and a control module, wherein the construction module is used for constructing a layered policy library, and the layered policy library comprises a base layer policy library, a scene layer policy library and a dynamic policy library; the system comprises a generation module, a detection module and a control module, wherein the generation module is used for generating an interference situation map based on a received interference signal, and the interference situation map comprises a feature vector and situation grade evaluation; The acquisition module is used for establishing a multi-level strategy screening mechanism, and acquiring anti-interference candidate strategies from the layered strategy library based on the interference situation map by the multi-level strategy screening mechanism, wherein the methods matched by strategy libraries of different levels are different; The determining module is used for constructing a comprehensive efficiency evaluation model and obtaining an optimal anti-interference strategy from each anti-interference candidate strategy through the comprehensive efficiency evaluation model; and the execution module is used for executing the optimal anti-interference strategy, issuing the optimal anti-interference strategy to the signal processing unit through the standard interface, and simultaneously monitoring the execution state