基于相位变化率的单站EKF无源定位算法研究

传统的无源定位方法主要是利用到达方位角（DOA）信息对雷达等辐射源进行测向交叉定位，但由于该方法对测角精度的敏感性，仅利用DOA信息会导致定位精度低，算法收敛时间长等不良后果。本文探讨了一种融入相位变化率（PRC）信息的推广卡尔曼滤波（EKF）算法，通过仿真，分析了DOA与PRC单独测量与联合测量对定位精度的影响，同时，将融入PRC信息的EKF定位算法与只测角定位算法进行了比较。

A Single-point EKF Passive Location Algorithm Based on Phase Rate of Change

In traditional passive location techniques to emitter as radar,the cross of direction lines by the use of DOA(direction of arrival) information is a main method.But the method maybe leads to worse accuracy or slower convergence. An EKF(Extended Kalman Filter) algorithm is discussed which adds PRC(Phase Rate of Change) information.Influence to location accuracy of DOA,PRC and DOA-PRC is analyzed respectively.And comparison between two algorithms is also given by the simulation results.