Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30222
Identification of Wideband Sources Using Higher Order Statistics in Noisy Environment

Authors: S. Bourennane, A. Bendjama

Abstract:

This paper deals with the localization of the wideband sources. We develop a new approach for estimating the wide band sources parameters. This method is based on the high order statistics of the recorded data in order to eliminate the Gaussian components from the signals received on the various hydrophones.In fact the noise of sea bottom is regarded as being Gaussian. Thanks to the coherent signal subspace algorithm based on the cumulant matrix of the received data instead of the cross-spectral matrix the wideband correlated sources are perfectly located in the very noisy environment. We demonstrate the performance of the proposed algorithm on the real data recorded during an underwater acoustics experiments.

Keywords: Higher-order statistics, high resolution array processing techniques, localization of acoustics sources, wide band sources

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1058439

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1249

References:


[1] S. Bourennane, A. Bendjama, "Locating wide band acoustic sources using higher-order statistics," Applied Acoustics, vol. 63, pp. 235-251, March 2002.
[2] A. Bendjama, S. Bourennane, "Enhanced broadband matched field processing through high resolution techniques," In CDROM (SAM2002), USA, 2002, pp. 179-183.
[3] J. A. Sunde, "Detection of a buried object under a water-sand interface," MSc thesis, Department of Telecommunication, Norwegian University of Science and Technology, Norway, 1999.
[4] N. Yuen and B. Friedlander, (1997, May). DOA estimation in multipath : an approach using fourth-order cumulants. IEEE. Trans. On Signal Processing, 45(5), pp. 1253--1263.
[5] Lean Yip, Joe C. Chen, Ralph E. Hudson, and Kung Yao, (2002, December). Cramer-Rao bound analysis of wideband source localization and DOA estimation. Proceedings of SPIE -- Volume 4791 Advanced Signal Processing Algorithms, Architectures, and Implementations XII, pp. 304-316.
[6] P. Stoica and A. Nehorai,(1989, May). MUSIC, Maximum Likelihood, and Cramér-Rao Bound. IEEE Trans. Acoust. Speech, Signal Processing, 37(5), pp. 720- 741.