The Optimal Kalman Type State Estimator With Multi-Step Correlated Process and Measurement Noises

摘要：

In this paper,an optimal Kalman type recursive state estimator is presented for the discrete time random dynamic system when the process noise and measurement noise are two-step correlated. Then,we extend it to the more general case of the process noise and measurement noise being n-step correlated. Finally,we verify that the Kalman type filter equation with one-step correlated process noise and measurement noise is globally optimal in the sense that its performance is the same as that of the optimal Mean Square Error state estimation using all observations from initial time up to now.

作者: Andi Fu Yunmin Zhu Enbin Song

作者单位: College of Mathematics Sichuan University,Chengdu,610064,China

会议类型: 国际会议

会议名称: The 2008 International Conference on Embedded Software and Systems Symposia(ICESS 2008)(2008国际嵌入式系统及嵌入式软件会议)

会议地点: 成都

会议语种:英文

页码: 215-220

在线出版日期: 2008-01-01（万方平台首次上网日期，不代表论文的发表时间）