Optimal filtering for systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements
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- 作者：Dongyan Chen ; a ; dychen_2004@aliyun.com" class="auth_mail" title="E-mail the corresponding author ; Long Xua ; b ; longxu19880319@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Junhua Duc
- 关键词：Linear optimal estimation ; Multiplicative noises ; Finite-step autocorrelated process noises ; Random one-step sensor delay ; Missing measurements
- 刊名：Communications in Nonlinear Science and Numerical Simulation
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：32
- 期：Complete
- 页码：211-224
- 全文大小：714 K
文摘
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We study the optimal filtering problem for time-varying systems with correlated noises and uncertain observations.
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We design an optimal Kalman filtering algorithm in the sense of minimum mean square error (MMSE).
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We propose a new Kalman filtering algorithm which is suitable for online applications.