Radar Jamming Decision Making Technology Based On Swarm Intelligence Algorithm

In the modern battlefield,radar technology and radar jamming technology have become the key issues for controlling the battlefield situation and determining success or failure.Radar jamming decision-making,as a prerequisite for radar jamming,is even more important.As more and more radar and jamming equipment are used by the both sides involved in the war,the radar jamming decision-making is prone to face the problem of combinatorial explosion.It is difficult to formulate jamming plans accurately for a large group of targets in a short time by using traditional methods.To solve the above problems,the following aspects have been studied:Firstly,the basic principles of radar jamming decision-making are studied,the prerequisites and components of radar jamming decision-making are discussed.The components required by the intelligent jamming decision-making system are discussed,including parameter library,knowledge base and decision reasoning engine.The jamming effect is explained.The basic criteria of jamming effect evaluation are described.Evaluation indicators are selected,and respective membership functions are established according to different indicators.Secondly,in view of the existing jamming decision model that cannot solve the problem of timing decision in a specific scenario,a two-level jamming decision model is proposed.Target allocation,jamming style selection and timing decision are completed at the same time.The composition structure of the jamming decision maker and the objective function of each level of jamming decision-making are given.The constraint conditions in three different jamming scenarios are separately discussed.The commonly used constraint condition processing methods are discussed,and a partial jamming effect evaluation method is given.The jamming decision-making model is filled with the jamming effect evaluation result.The rationality of the swarm intelligence algorithm applied to the radar jamming decision-making optimization problem is analyzed.Then,two typical examples of classical swarm intelligence algorithms are studied,namely genetic algorithm and artificial bee colony algorithm.The basic ideas and concepts of the algorithm are explained respectively.The basic process of the algorithm,the influence of parameters,the advantages and disadvantages of the algorithm are discussed.An repair-based operator improvement method is proposed,which makes the improved algorithm operators suitable for solving radar jamming decision-making problems.The feasibility of swarm intelligence algorithm in radar jamming decision-making problems is verified through simulation experiments.Finally,in view of the shortcomings of the classical swarm intelligence algorithm,an artificial bee colony algorithm based on immune genetic simulated annealing is proposed.The improved operators are used in the new algorithm which makes the new algorithm suitable for solving radar jamming decision-making problems.An individual concentration calculation method based on Jaccard similarity is proposed to control the population diversity.The simulated annealing mechanism is introduced,in order to search around the poor-quality solutions with a certain probability,thereby increasing the probability of obtaining high-quality solutions.The basic idea and principle of the algorithm are analyzed,the specific algorithm flow and steps are given,and the parameters of the algorithm are analyzed.The jamming scenarios and models for coordinated penetration are established.The new algorithm is used to solve the optimization problem of radar jamming decision-making in the above scenarios.The correctness and superiority of the algorithm are verified by simulation experiments.