目标运动要素自主隐蔽解析的微分进化策略

Differential evolution strategy for autonomous concealment analysis of target motion elements

针对传统目标运动要素自主隐蔽解析中存在的噪声适应性差等问题,提出要素自主解析的微分进化策略。首先,简要论述了目标运动要素的自主隐蔽解析过程;其次,推导要素自主解析的协方差传播过程,给出目标运动要素方差与目标观测方位方差的对应关系,分析方位观测均方差对要素自主解析结果的影响;再次,提出了微分进化算法对自主解析模型的优化策略;最后,对优化策略进行仿真验证。结果表明,当方位存在0.1°的均方误差时,初距D0均方误差约为12 Cab,速度分量Vmx、Vmy均方误差分别约为5 Kn、6 Kn,通过微分进化策略优化后明显提高了要素自主解析结果的精度。

Aiming at the problem of poor noise adaptability in the independent concealment analysis of the traditional target motion elements,a differential evolution strategy of factor autonomous analysis is proposed.Firstly,the autonomous concealment analysis process of the target motion elements is briefly discussed.Secondly,the covariance propagation process of the autonomous analysis of the elements is derived,the corresponding relationship between the target motion element variance and the target observation azimuth variance is given,and the influence of azimuth observation mean square error is analyzed.Then a differential evolution algorithm on the autonomous analytical model is proposed again.Finally,the optimization strategy is verified by simulation.The results show that when the azimuth error of 0.1°exists in the azimuth,the mean square error of the initial distance D0 is about 12 Cab,and the mean square errors of the velocity components Vmx and Vmy are about 5 Kn and 6 Kn respectively.The accuracy of the elements autonomous analysis is obviously improved by the optimization of the differential evolution strategy.