A Matched Field Processing Based on Compressed Sensing
- Yingchun Chen, Yali Jiang, Biao Wang
- Corresponding Author
- Yingchun Chen
Available Online June 2017.
- https://doi.org/10.2991/ammee-17.2017.50How to use a DOI?
- Underwater Acoustic Localization; Compressed Sensing; Matched Field Processing; Sparse Reconstruction
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - Advances in Materials, Machinery, Electrical Engineering (AMMEE 2017) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/ammee-17.2017.50 DO - https://doi.org/10.2991/ammee-17.2017.50 ID - Chen2017/06 ER -