Recursive Hybrid Cramér–Rao Bound for Discrete-Time Markovian Dynamic Systems

Author

Chengfang Ren ; Galy, Jerome ; Chaumette, Eric ; Vincent, Francois ; Larzabal, Pascal ; Renaux, Alexandre

Author_Institution

LSS 3, Univ. Paris-Sud, Orsay, France

Volume

22

Issue

10

fYear

2015

fDate

Oct. 2015

Firstpage

1543

Lastpage

1547

Abstract

In statistical signal processing, hybrid parameter estimation refers to the case where the parameters vector to estimate contains both non-random and random parameters. As a contribution to the hybrid estimation framework, we introduce a recursive hybrid Cramér-Rao lower bound for discrete-time Markovian dynamic systems depending on unknown deterministic parameters. Additionally, the regularity conditions required for its existence and its use are clarified.

Keywords

Markov processes; array signal processing; discrete time systems; recursive estimation; statistical analysis; discrete time Markovian dynamic system; hybrid parameter estimation; nonrandom parameter estimation; parameter vector estimation; random parameter estimation; recursive hybrid Cramer-Rao lower bound; statistical signal processing; unknown deterministic parameter; Bayes methods; Electronic mail; Estimation; Indexes; Noise; Parameter estimation; Vectors; Parameter estimation; dynamic Markovian systems; estimation error lower bound;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2015.2412173

Filename

7059216