遗传算法在弹道数据融合中的应用

Application of Genetic Algorithms in Trajectory Data Fusion

目前靶场采用全测元融合滤波的方式确定目标飞行器弹道,为测控设备提供引导信息并为安全决策和指挥显示提供数据支持。随着靶场测控设备种类和数量越来越丰富,而新的试验任务又对实时弹道融合解算精度提出了更高的要求,全测元融合处理能否提供高精度的融合弹道和快速地从海量融合方案中寻找最优的方案是弹道测量数据融合急需解决的问题。本文提出了基于遗传算法的最优融合方案选择方法,利用该方法得到的融合弹道精度优于全测元融合方案,仿真结果表明了方法的有效性。

Measurement data is currently used to determine fusion trajectory and then calculate guidance data and support safety control and command display.With increasing types and quantity of TTC equipment and higher and higher requirements of experiment missions on trajectory accuracy,it becomes more and more demanding for the traditional fusion scheme of all measurement-elements to determine high accuracy fusion trajectory and find the best fusion scheme from mass number of schemes in a timely manner.A method to determine the best fusion scheme based on genetic algorithm is presented in this paper and the fusion trajectory accuracy is significantly improved.Simulation results verify the effectiveness of the method.