Research On Jamming Benefit Evaluation And Jamming Decision Algorithm In Cognitive Confrontation

For the future information confrontation,electronic confrontation is gradually replacing the traditional war mode as the main form of war.A single jamming mode is not effective due to the complex electromagnetic environment.Selecting the appropriate jamming decision to coordinately allocate the jamming resources is the development direction of the electronic countermeasures.In cognitive confrontation,accurate assessment of jamming benefits and correct interference decision-making schemes are of great significance for improving the operational efficiency of the entire cognitive confrontation system.Since the main task of the radar in the battlefield environment is to achieve the detection,location and tracking of the target,this paper refers to the existing research methods,and establishes the evaluation model based on the discovery probability and positioning accuracy of the radar network.Considering the characteristics and the main influencing factors of radar signals,the jamming power,jamming frequency,jamming timing and jamming pattern are selected as the membership function to study the relationship between jamming benefit and distance,false alarm probability and different jamming strategies.The simulation results show that the appropriate false alarm probability,close distance and appropriate jamming strategy all can improve the jamming effect and provide a theoretical basis for obtaining the best jamming effect on the actual battlefield.In the single-objective jamming decision-making algorithm,this paper proposes an improved artificial bee colony algorithm based on tabu search,since the parameters in existing commonly used algorithms depend heavily on manual selection which are lack of objectivity and credibility.It introduces the tabu list into artificial bee colony algorithm to reduce the unnecessary iterative process and it is not easy to fall into a local optimum.Simulation results show that the search ability and probability of finding the optimal solution of the new algorithm are better than the other two.Most of the existing studies about jamming decision only pay attention to the jamming benefits,while ignoring the jamming cost.Against the issue,this paper introduces the concept of jamming cost in the cognitive collaborative jamming decision model and refines it as a multi-objective one.Based on the artificial bee colony algorithm in the target decision of the bill of lading,it is transformed into a multi-objective artificial bee colony algorithm and applied to the multi-objective decision problem,and compared with the commonly used NSGA-II algorithm in multi-objective problems.The simulation results show that the multi-objective artificial bee colony algorithm can obtain the Pareto optimal solution set that meets the requirements in multiobjective decision making,which has strong superiority.