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Underwater Acoustic Intensity Field Reconstruction by Kriged Compressive Sensing
Sun J(孙洁)1,2; Yu JC(俞建成)1; Zhang AQ(张艾群)1; Song AJ(宋爱军)3; Zhang FM(张福民)4
Department海洋机器人卓越创新中心
Conference Name13th ACM International Conference on Underwater Networks and Systems, WUWNet 2018
Conference DateDecember 3-5, 2018
Conference PlaceShenzhen, China
Author of SourceCSSC Systems Engineering Research Institute ; Institute of Acoustics, Chinese Academy of Sciences ; Jilin University ; Northwestern Polytechnical University ; Shenzhen University
Source PublicationProceedings of the 13th ACM International Conference on Underwater Networks and Systems, WUWNet 2018
PublisherACM
Publication PlaceNew York
2018
Pages1-8
Indexed ByEI
EI Accession number20190306385948
Contribution Rank1
ISBN978-1-4503-6193-4
Keywordcompressive sensing kriging underwater acoustic sensing underwater gliders
AbstractThis paper presents a novel Kriged Compressive Sensing (KCS) approach for the reconstruction of underwater acoustic intensity fields sampled by multiple gliders following sawtooth sampling patterns. Blank areas in between the sampling trajectories may cause unsatisfying reconstruction results. The KCS method leverages spatial statistical correlation properties of the acoustic intensity field being sampled to improve the compressive reconstruction process. Virtual data samples generated from a kriging method are inserted into the blank areas. We show that by using the virtual samples along with real samples, the acoustic intensity field can be reconstructed with higher accuracy when coherent spatial patterns exist. Corresponding algorithms are developed for both unweighted and weighted KCS methods. By distinguishing the virtual samples from real samples through weighting, the reconstruction results can be further improved. Simulation results show that both algorithms can improve the reconstruction results according to the PSNR and SSIM metrics. The methods are applied to process the ocean ambient noise data collected by the Sea-Wing acoustic gliders in the South China Sea.
Language英语
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/23778
Collection海洋机器人卓越创新中心
Corresponding AuthorSun J(孙洁)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of SciencesShenyang,110016, P.R.China
2.University of Chinese Academy of Sciences, Beijing, 100049, P.R.China
3.Department of Electrical Engineering, University of Alabama, Tuscaloosa, Alabama 35487, USA
4.School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
Recommended Citation
GB/T 7714
Sun J,Yu JC,Zhang AQ,et al. Underwater Acoustic Intensity Field Reconstruction by Kriged Compressive Sensing[C]//CSSC Systems Engineering Research Institute, Institute of Acoustics, Chinese Academy of Sciences, Jilin University, Northwestern Polytechnical University, Shenzhen University. New York:ACM,2018:1-8.
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