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Conference Papers Year : 2015

A constrained hybrid Cramér-Rao bound for parameter estimation

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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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Dates and versions

hal-01234924 , version 1 (27-11-2015)

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Cite

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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