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.