Optimal filtering for systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements

被引:42
作者
Chen, Dongyan [1 ]
Xu, Long [1 ,2 ]
Du, Junhua [3 ]
机构
[1] Harbin Univ Sci & Technol, Dept Appl Math, Harbin 150080, Peoples R China
[2] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150001, Peoples R China
[3] Qiqihar Univ, Coll Sci, Qiqihar 161006, Peoples R China
来源
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION | 2016年 / 32卷
基金
中国国家自然科学基金;
关键词
Linear optimal estimation; Multiplicative noises; Finite-step autocorrelated process noises; Random one-step sensor delay; Missing measurements; MULTIPLE PACKET DROPOUTS; TIME-VARYING SYSTEMS; SLIDING-MODE CONTROL; STOCHASTIC NONLINEARITIES; OCCURRING UNCERTAINTIES; FADING MEASUREMENTS; NETWORKED SYSTEMS; ESTIMATORS; SUBJECT;
D O I
10.1016/j.cnsns.2015.08.015
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The optimal filtering problem is investigated for a class of discrete stochastic systems with finite-step autocorrelated process noises, random one-step sensor delay and missing measurements. The random disturbances existing in the system are characterized by the multiplicative noises and the phenomena of sensor delay and missing measurements occur in a random way. The random sensor delay and missing measurements are described by two Bernoulli distributed random variables with known conditional probabilities. By using the state augmentation approach, the original system is converted into a new discrete system where the random one-step sensor delay and missing measurements exist in the sensor output. The new process noises and observation noises consist of the original stochastic terms, and the process noises are still autocorrelated. Then, based on the minimum mean square error (MMSE) principle, a new linear optimal filter is designed such that, for the finite-step autocorrelated process noises, random one-step sensor delay and missing measurements, the estimation error is minimized. By solving the recursive matrix equation, the filter gain is designed. Finally, a simulation example is given to illustrate the feasibility and effectiveness of the proposed filtering scheme. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:211 / 224
页数:14
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