Optimal filtering and smoothing for discrete-time stochastic singular systems

被引：60

作者：

Sun, Shu-Li ^{[1
]}

Ma, Jing ^{[1
]}

机构：

[1] Heilongjiang Univ, Dept Automat, Harbin 150080, Peoples R China

来源：

SIGNAL PROCESSING | 2007年 / 87卷 / 01期

基金：

中国国家自然科学基金;

关键词：

full-order estimators; projection theory; correlated noise; prediction; filtering; smoothing; stochastic singular system;

D O I：

10.1016/j.sigpro.2006.05.007

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

A stochastic singular system with correlated noises at the same time is transferred to the equivalent nonsingular system with correlated noises at the same and neighboring time. Applying time-domain innovation analysis method, the recursive full-order predictor, filter and smoother are presented for this nonsingular system. Further, the full-order filter and smoother are given for original stochastic singular linear systems with correlated noises. Recursive and nonrecursive computational formulas for estimation error covariance matrices are given. Furthermore, the steady-state filter and smoother are also investigated. The asymptotic stability is proved. All results generalize the standard Kalman filtering. A simulation example shows the effectiveness. (c) 2006 Elsevier B.V. All rights reserved.

引用

页码：189 / 201

页数：13

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