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Underwater Acoustic Field Reconstruction Using a Compressive Sensing Approach
Sun J(孙洁); Song, Aijun; Yu JC(俞建成); Zhang AQ(张艾群); Zhang FM(张福民)
作者部门海洋机器人卓越创新中心
会议名称OCEANS 2017 MTS/IEEE Anchorage
会议日期September 18-21, 2017
会议地点Anchorage, USA
会议录名称OCEANS 2017 MTS/IEEE Anchorage
出版者IEEE
出版地New York
2017
页码1-5
收录类别EI
EI收录号20182405299314
产权排序1
ISBN号978-0-692-94690-9
摘要

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.

语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21294
专题海洋机器人卓越创新中心
通讯作者Sun J(孙洁)
作者单位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
推荐引用方式
GB/T 7714
Sun J,Song, Aijun,Yu JC,et al. Underwater Acoustic Field Reconstruction Using a Compressive Sensing Approach[C]. New York:IEEE,2017:1-5.
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