The Marginal Enumeration Bayesian Cramer-Rao Bound for Jump Markov Systems

被引：7
|
作者：
Fritsche, Carsten [1 ]
Orguner, Umut [2 ]
Svensson, Lennart [3 ]
Gustafsson, Fredrik [4 ]
机构：
[1] IFEN GmbH, D-85586 Poing, Germany
[2] Middle E Tech Univ, Dept Elect & Elect Engn, TR-06531 Ankara, Turkey
[3] Chalmers Univ Technol, Dept Signals & Syst, S-41296 Gothenburg, Sweden
[4] Linkoping Univ, Dept Elect Engn, Div Automat Control, SE-58183 Linkoping, Sweden
来源：
IEEE SIGNAL PROCESSING LETTERS | 2014年 / 21卷 / 04期
关键词：
Jump markov systems; performance bounds; statistical signal processing; PERFORMANCE; FILTER;
D O I：
10.1109/LSP.2014.2305115
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 marginal version of the enumeration Bayesian Cramer-Rao Bound (EBCRB) for jump Markov systems is proposed. It is shown that the proposed bound is at least as tight as EBCRB and the improvement stems from better handling of the nonlinearities. The new bound is illustrated to yield tighter results than BCRB and EBCRB on a benchmark example.
引用
收藏
页码：464 / 468
页数：5
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