A Matched Field Processing Based on Compressed Sensing

DOI

10.2991/ammee-17.2017.50How to use a DOI?

Keywords

Underwater Acoustic Localization; Compressed Sensing; Matched Field Processing; Sparse Reconstruction

Abstract

The traditional MFP (matched field processing, MFP) methods of underwater acoustic target often have poor estimation performance or get inaccurate estimation result on the constrain of spatial sparse observation. Considering the problem, this paper proposed a new high-accuracy MFP estimation algorithm of underwater acoustic target based on compressed sensing by analyzing the space sparsity of underwater target location. The algorithm established the spatial sparse description model of underwater target, and compressed sensing the underwater target in spatial domain, then used the joint sparse reconstruction algorithm to achieve the MFP estimation of underwater acoustic target. The simulation results show that the method can increase the DOA estimation accuracy of underwater acoustic target at less array elements and less snapshots.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yingchun Chen
AU  - Yali Jiang
AU  - Biao Wang
PY  - 2017/06
DA  - 2017/06
TI  - A Matched Field Processing Based on Compressed Sensing
BT  - Proceedings of the Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017)
PB  - Atlantis Press
SP  - 254
EP  - 258
SN  - 2352-5401
UR  - https://doi.org/10.2991/ammee-17.2017.50
DO  - 10.2991/ammee-17.2017.50
ID  - Chen2017/06
ER  -