Memetic优化的外辐射源雷达方位-多普勒定位方法

针对外辐射源雷达系统中快速高精度定位信息不易得到的问题,提出一种基于文化基因(Memetic)优化的方位-多普勒联合定位算法,首次将Memetic算法引入外辐射源定位领域,并设计了一种新的下降方向作为Memetic局部搜索策略,把目标定位转化成函数优化问题.实验结果显示,在无先验初始点信息和单次观测条件下,新算法不仅能将相对定位误差控制在较小范围内,而且能使定位精度稳定地逼近克拉美罗界.相比采用传统进化算法解决定位问题,新方法能够以更快的速度收敛到最优解,且单次定位时间更短,精度更高,从而实现对目标位置的快速高精度定位.

Novel passive radar location algorithm based on Memetic optimization by using the bearing-and-Doppler frequency

As the fast and high accurate location information is difficult to obtain in passive radar systems,this paper proposes a passive radar location algorithm based on Memetic optimization by using the bearing-and-Doppler frequency,which is the first time to introduce the Memetic algorithm to the passive location field.With a newly designed decreasing direction as the Memetic local search strategy,the target location is transformed to a problem of function optimization.Experimental results validate that the new algorithm,realizing a fast and high accurate target location,can not only retain the relative error under a low level so that the location accuracy can approach the Cramer-Rao Bound steadily,but also converge to the optimal solution more rapidly than evolutionary algorithm location.