Recursive State Estimation for Linear Systems with General Correlated Measurement Noises
Han Chongzhao¹, Wang Jie¹, LiXiaorong²
(1. Xi'an Jiaotong University,  Xi'an 710049, China; 2. University of New Orleans,'USA)

Abstract: In order to obtain the recursive filtering algorithm for a linear system with general correlated measurement noises, the problem is transformed to that of filtering for a single random vector with correlated measurements. According to the linear unbiased minimum variance estimation algorithm for a single random vector, a recursive filtering algorithm ispresented. A digital simulation technique is used such that the new algorithm can be compared with the Kalman filtering algorithm, assuming that the measurement noises are uncorrelated. Validity of the proposed algorithm is thus proved.
Keywords: general correlated noise;linear unbiased minimum variance estimation;Kalman filtering