Underwater Acoustic Field Reconstruction Using a Compressive Sensing Approach | |
Sun J(孙洁)![]() ![]() ![]() | |
Department | 海洋机器人前沿技术中心 |
Conference Name | OCEANS 2017 MTS/IEEE Anchorage |
Conference Date | September 18-21, 2017 |
Conference Place | Anchorage, USA |
Source Publication | OCEANS 2017 MTS/IEEE Anchorage |
Publisher | IEEE |
Publication Place | New York |
2017 | |
Pages | 1-5 |
Indexed By | EI ; CPCI(ISTP) |
EI Accession number | 20182405299314 |
WOS ID | WOS:000455012000322 |
Contribution Rank | 1 |
ISBN | 978-0-692-94690-9 |
Abstract | In this paper, we apply a block-based compressive sensing (BCS) architecture to address the reconstruction of underwater acoustic intensity fields. Although with anisotropic characteristics, underwater acoustic intensity fields can be compressed or represented in sparse transform domains. The distinct advantages of the BCS method include no need for any prior knowledge of the interested acoustic fields and no need for complete sampling coverage. Both benefits can facilitate experimentation and improve reconstruction precision. We demonstrated the recovery capability by applying this algorithm to the reconstruction of simulated acoustic fields in the Gulf of Mexico, where the bathymetry and water column showed high levels of spatial variability. Further, a field experiment was conducted at a local river, Lake Tamaha, where an autonomous underwater vehicle navigated during acoustic transmissions. Reconstruction performance comparisons were made between the BCS and interpolation methods at different measurement ratios. |
Language | 英语 |
Citation statistics | |
Document Type | 会议论文 |
Identifier | http://ir.sia.cn/handle/173321/21294 |
Collection | 海洋机器人前沿技术中心 |
Corresponding Author | Sun J(孙洁) |
Affiliation | 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang,110016, P.R.China 2.University of Chinese Academy of Sciences, Beijing, 100049, P.R.China 3.School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA 4.Department of Electrical Engineering, University of Alabama, Tuscaloosa, Alabama 35487, USA |
Recommended Citation GB/T 7714 | Sun J,Song AJ,Yu JC,et al. Underwater Acoustic Field Reconstruction Using a Compressive Sensing Approach[C]. New York:IEEE,2017:1-5. |
Files in This Item: | ||||||
File Name/Size | DocType | Version | Access | License | ||
Underwater Acoustic (3725KB) | 会议论文 | 开放获取 | CC BY-NC-SA | View Application Full Text |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment