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.

Keywords: Equality constraints; Parameter estimation; Hybrid Cramér-Rao bounds

Domains: Computer Science [cs]; Signal and Image Processing

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⟩