Sequential estimation of the range and the bearing using the zero-forcing MUSIC approach

Abstract : In this paper, we consider the range and bearing estimation of near-field narrow-band sources from noisy data observed across a passive sensor array. For some difficult scenarios as for correlated and largely spaced sources at low SNRs, or correlated and closely spaced sources, the Near FieLd (NFL) version of the MUltiple SIgnal Classification (MUSIC) algorithm is no longer reliable. In this paper, we adapt and extend the sequential Zero-Forcing MUSIC (ZF-MUSIC) algorithm, which avoids the delicate search of multiple maxima, to the NFL context. In order to compare the NFL ZF-MUSIC with the Second-Order Statistics Weighted Prediction (SOS-WP) algorithm, we assumed an uniform sampling in the spatial domain. However, the proposed algorithm can be exploited for general array geometries. Finally numerical simulations show that the variance of the proposed algorithm achieves the Cram'er-Rao Bound (CRB) in difficult scenarios and for sufficient Signal to Noise Ratio (SNR).
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Communication dans un congrès
The 17th European Signal Processing Conference, (EUSIPCO'09), 2009, Glasgow, European Union. pp.1-5, 2009
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https://hal.inria.fr/inria-00445463
Contributeur : Mohammed Nabil El Korso <>
Soumis le : vendredi 8 janvier 2010 - 15:29:46
Dernière modification le : jeudi 5 avril 2018 - 12:30:04
Document(s) archivé(s) le : jeudi 17 juin 2010 - 20:24:02

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  • HAL Id : inria-00445463, version 1

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Mohammed Nabil El Korso, Guillaume Bouleux, Remy Boyer, Sylvie Marcos. Sequential estimation of the range and the bearing using the zero-forcing MUSIC approach. The 17th European Signal Processing Conference, (EUSIPCO'09), 2009, Glasgow, European Union. pp.1-5, 2009. 〈inria-00445463〉

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