An Optimal Sequential Filter for the Linear System with Correlated Noises
The sequential filter is a kind of useful estimate fusion algorithm. Traditional sequential filters are mainly utilized for the linear systems with the assumption of uncorrelated noises. Recently, some effective algorithms have been presented for the linear system with multiple sensors and correlated noises. Unfortunately, they cant perfectly solve the optimal filtering estimate in Linear Minimum Mean Square Error (LMMSE) for the systems with correlative measurement noises which are also cross-correlated with the process noise one time step apart and seldom discussed in present researches. And a novel sequential filter, which is optimal in LMMSE, is proposed in this paper for the linear dynamic system with correlative measurement noises which are also cross-correlated with the process noise one time step apart. The kernel of the novel optimal sequential filter is to decorrelate these correlations by use of the equivalent measurement function. Synchronously, the computer simulations are also presented to illustrate its performance.
Information fusion Correlated Noises Decorrelation Sequential Filter Linear Minimum Mean Square Error(LMMSE)
Xiao-liang Feng Quan-bo Ge Cheng-lin Wen
Institute of information and control,Hangzhou Dianzi University Hangzhou,Zhejiang,P.R China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
5073-5078
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）