Kalman Filtering With Multiplicative and Additive Noises

被引：0
|
作者：
Wu, Yilin [1 ,3 ]
Shen, Zhiping [2 ]
Zhang, Qian [3 ]
Liu, Yu [1 ]
机构：
[1] S China Univ Technol, Coll Automat Sci & Technol, Guangzhou 510640, Guangdong, Peoples R China
[2] Henan Normal Univ, Dept Math & Informat Sci, Henan 453007, Peoples R China
[3] Guangdong Univ Educ, Dept Comp Sci, Guangzhou 510310, Guangdong, Peoples R China
来源：
PROCEEDINGS OF THE 2013 ASIA-PACIFIC COMPUTATIONAL INTELLIGENCE AND INFORMATION TECHNOLOGY CONFERENCE | 2013年
基金：
中国国家自然科学基金;
关键词：
SYSTEMS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper issues the problem of performing Kalman filtering for discrete-time stochastic linear (DTSL) systems. Multiplicative and additive noise is considered in the system model. An optimal Kalman filter for the DTSL system is designed based on the standard Kalman filter. For Optimal Kalman filter, we also study the statiscal convergence properties of the estimation error covariance. The results are illustrated with examples.
引用
收藏
页码：420 / 426
页数：7
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