A constrained hybrid Cramér-Rao bound for parameter estimation

Chengfang Ren (1) , Julien Le Kernec (2) , Jérôme Galy (3) , Eric Chaumette (4) , Pascal Larzabal (5) , Alexandre Renaux (1)

1 L2S - Laboratoire des signaux et systèmes
2 University of Nottingham Ningbo [China]
3 LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
4 ISAE-SUPAERO - Institut Supérieur de l'Aéronautique et de l'Espace
5 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. Numerous works have shown the versatility of deterministic constrained Cramér-Rao bound for estimation performance analysis and design of a system of measurement. However in many systems both random and non-random parameters may occur simultaneously. In this communication, we propose a constrained hybrid lower bound which take into account of equality constraint on deterministic parameters. The usefulness of the proposed bound is illustrated with an application to radar Doppler estimation.

Mots clés: Equality constraints; Parameter estimation; Hybrid Cramér-Rao bounds

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

Chengfang Ren, Julien Le Kernec, Jérôme Galy, Eric Chaumette, Pascal Larzabal, et al.. A constrained hybrid Cramér-Rao bound for parameter estimation. ICASSP: International Conference on Acoustics, Speech and Signal Processing, Apr 2015, Brisbanne, Australia. pp.3472-3476, ⟨10.1109/ICASSP.2015.7178616⟩. ⟨hal-01234924⟩