Recursive hybrid Cramer-Rao bound for discrete-time Markovian dynamic systems

Chengfang Ren (1) , Jérôme Galy (2) , Eric Chaumette (3) , François Vincent (3) , Pascal Larzabal (4) , Alexandre Renaux (1)

1 L2S - Laboratoire des signaux et systèmes
2 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 DEOS - Département Electronique, Optronique et Signal
4 SATIE - Systèmes et Applications des Technologies de l'Information et de l'Energie

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 bounds for discrete-time Markovian dynamic systems depending on unknown determinis-tic parameters. Additionnally, the regularity conditions required for its existence and its use are clarified.

Mots clés: Dynamic Markovian systems; Parameter estimation; Estimation error lower bound

Domaines: Traitement du signal et de l'image [eess.SP]

Chengfang Ren, Jérôme Galy, Eric Chaumette, François Vincent, Pascal Larzabal, et al.. Recursive hybrid Cramer-Rao bound for discrete-time Markovian dynamic systems. IEEE Signal Processing Letters, 2015, 22 (10), pp.1543-1547. ⟨10.1109/LSP.2015.2412173⟩. ⟨hal-01226835⟩