中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Underwater Acoustic Intensity Field Reconstruction by Kriged Compressive Sensing

文献类型:会议论文

作者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
出版日期2018
会议日期December 3-5, 2018
会议地点Shenzhen, China
关键词compressive sensing kriging underwater acoustic sensing underwater gliders
页码1-8
英文摘要This 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.
源文献作者CSSC Systems Engineering Research Institute ; Institute of Acoustics, Chinese Academy of Sciences ; Jilin University ; Northwestern Polytechnical University ; Shenzhen University
产权排序1
会议录Proceedings of the 13th ACM International Conference on Underwater Networks and Systems, WUWNet 2018
会议录出版者ACM
会议录出版地New York
语种英语
ISBN号978-1-4503-6193-4
源URL[http://ir.sia.cn/handle/173321/23778]  
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.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
推荐引用方式
GB/T 7714
Sun J,Yu JC,Zhang AQ,et al. Underwater Acoustic Intensity Field Reconstruction by Kriged Compressive Sensing[C]. 见:. Shenzhen, China. December 3-5, 2018.

入库方式: OAI收割

来源:沈阳自动化研究所

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