Design And Implementation Of Radar Reconnaissance Route Planning Algorithm

In recent years,because of the terrain constraint,the detection ability of ground radar which is in base station has been decreasing,the airborne radar is playing a more and more important role in a reconnaissance miss.And path planning is the key to the reconnaissance mission.Right now,there are many algorithms for the reconnaissance mission,but this article is going to choose genetic algorithm to solve the problem.But the traditional genetic algorithm is not applicable to this case,because the traditional genetic algorithm's demand for space is too high and convergence time is too long,especially when environmental constraints of the problem is very complicate.So this article improves the traditional genetic algorithm.Besides,there is also an evolutionary multi-objective optimization algorithm proposed in this article.In this article,we will study the path planning of reconnaissance mission based on airborne radar for target area and target point.Besides the introduction of the background and significance of the issue in the beginning of the article,this article models the issues of the radar reconnaissance mission.Those issues are based on several constraints and threats of backgrounds including environment model and reconnaissance aircraft's self-constraint,such as meteorological conditions and the threats of enemy's radar.Then this article analyses regional coverage control method and designs a new method for the complicate environment.When finishing the environment modeling,an algorithm based on genetic algorithm and an evolutionary multi-objective optimization algorithm are proposed for radar reconnaissance mission.In the improved genetic algorithm,population initialization method changes from random to heuristics.The fitness function chooses penalty function and there are five operators designed according to the characteristics of the problem.After that,the article designs an evolutionary multi-objective optimization algorithm whose gene coding is the same as the improved genetic algorithm which is based on real number.And for the fitness part,it uses the Pareto domination which is used for screening individuals.Its mutation operators is also specially designed.At last,a series of simulations and experimental tests are carried out,and the result shows that the algorithms are reasonable,feasible and reliable.