测角目标定位的协方差矩阵旋转变换滤波算法

A Rotated Covariance Extended Kalman Filter Algorithm for Angle-Only Position Estimation

基于滤波量比预测量和测量量都准确这一原理 ,该文提出一种适用于只测角无源定位的非线性滤波算法———协方差矩阵旋转变换的推广Kalman滤波算法 .文中推导了协方差矩阵变换的原理 ,给出了二维只测角无源定位应用的协方差矩阵旋转变换公式 .仿真表明该算法比同类型的基于微分线性化和泛线性化的Kalman滤波算法具有更好的性能 .

A rotated covariance extended Kalman filter algorithm which is very useful for emitter passive localization and tracking is presented in this paper.The rotation transformation on covariance matrix of extended Kalman filter subtly handles the nonlinear problem in stochastic estimation problems with simplicity.In this paper,principle of rotated covariance is derived first,then detailed algorithms for 2D passive localization are developed.Experimental results show that the proposed algorithm is better than those linearization by differentiation based extended Kalman filter and universal linearization concept based extended Kalman filter.