Memetic优化的外辐射源雷达方位-多普勒定位方法  

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

作　　者：同非[1] 王俊[1] 李红伟[1] 

机构地区：[1]西安电子科技大学雷达信号处理国家重点实验室,陕西西安710071

出　　处：《西安电子科技大学学报》2012年第4期46-51,102,共7页Journal of Xidian University

基　　金：国家自然科学基金资助项目(60472087);国家部委科技预研基金资助项目(9140C0105071006)

摘　　要：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.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.

关 键 词：无源雷达 文化基因算法 局部搜索 克拉美罗界 进化算法 

分 类 号：TN958.97[电子电信—信号与信息处理]