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A constrained hybrid Cramér-Rao bound for parameter estimation

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. 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.
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Submitted on : Friday, November 27, 2015 - 2:02:31 PM
Last modification on : Wednesday, October 5, 2022 - 11:12:07 AM
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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⟩



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