A Matched Field Processing Based on Compressed Sensing

Content Provider	Semantic Scholar
Author	Chen, Yingchun Jiang, Yali Wang, Biao
Copyright Year	2017
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.
File Format	PDF HTM / HTML
DOI	10.2991/ammee-17.2017.50
Alternate Webpage(s)	https://download.atlantis-press.com/article/25878405.pdf
Alternate Webpage(s)	https://doi.org/10.2991/ammee-17.2017.50
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article