Research On Optimization Assignment For Cooperative Jamming Resources Based On Improved Genetic Algorithms

As the development of science and technology, modern warfare's situation has evolved from the traditional large-scale to the local small-scale war, and the ways to combat have turned from the original centralized control into a combination of electronic attack and concentrated firepower based on the electronic reconnaissance. With the continuous change of the battlefield environment and the advance of the weapons, the confrontation environment has become more and more difficult and the single-arms or single system has been unable to meet the operational conditions. So we need to coordinate resources across multiple platforms, and form the countermeasures system with a stronger fighting capability. This paper presented the research methods and results of the cooperative jamming resource assignment in the domestic and overseas field, and carried on discussion and research on the genetic algorithm concerning its current development situation, significance and the advantage.Explained the genetic algorithm, its process, and the algorithm parameter selection was provided. This paper described the selection operator, crossover operator, mutation operator, and the relationship among them. Finally, we discussed the convergence of the genetic algorithm, and proposed several solutions.Introduced the extended encoding method, on the basis of the real number coding scheme. It can solve the problem that the number of devices is not equal to the number of cases of enemy targets. In the solution, the selection operator, crossover operator and mutation operator of the simple genetic algorithm are improved, which enhance the speed of evolution population, and avoid the problem of falling into local convergence.At last, this paper constructs a jamming efficiency evaluation for jammer to radar, and gives the quantizing calculation model of each evaluation index; then uses the analytic hierarchy process to scientifically assign the weight of each evaluation index. On this basis, we present a multi-index comprehensive evaluation model of jamming efficiency for jammer to radar. Finally, we use the improved genetic algorithm based on the dynamic cross rate and dynamic mutation rate, which not only maintain the diversity of the population, but also avoid the premature convergence problem. The example is analyzed and the simulation results have shown that the improved genetic algorithm is valid and verified that the cooperative jamming strategy has some practical value.