Kalman Filtering with Intermittent Observations: Bounds on the Error Covariance Distribution

被引：0

作者：

Rohr, Eduardo ^{[1
]}

Marelli, Damian ^{[1
]}

Fu, Minyue ^{[1
]}

机构：

[1] Univ Newcastle, Sch Elect Engn & Comp Sci, Callaghan, NSW 2308, Australia

来源：

2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC) | 2011年

关键词：

PERFORMANCE;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

When measurements are subject to random losses, the covariance of the estimation error of a state estimator becomes a random variable. In this paper we present bounds on the cumulative distribution function of the covariance of the estimation error for a discrete time linear system. We also show that the bounds can be arbitrarily tight if sufficient computational power is available. Numerical simulations show that the proposed method provides tighter bounds than the ones available in the literature.

引用

页码：2416 / 2421

页数：6

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