ECE Spring Seminar Series

This is a past event

SPC Speaker, Lin Wan, University of Delaware


Title: Remote sensing of the shallow-water ocean environment using underwater sound waves



Around 70% of the Earth's surface is covered by ocean water. Shallow water regions, found on the continental shelf, are important to human activities (e.g. shipping, fishing, oil production). Studying the shallow-water environment is a stimulating and exciting discipline for oceanographers, engineers, and physicists. While in-situ measurements of the environment are spatially limited and satellite/airborne remote sensing data are severely undersampled in time, underwater sound waves traveling greater distances than electromagnetic waves in the ocean can be exploited to estimate seafloor properties and to monitor spatial and temporal variability of the ocean surface and the water column. Acoustic remote sensing involves sound source detection, localization, signal recovery, and environmental inversion. This talk is exclusively dedicated to estimates of sound speed and attenuation in marine sediments using underwater acoustic signals, namely, geo-acoustic inversion. The at-sea experiment of this research has been conducted in the New England Mud Patch region from the beginning of March to early April 2017. The collected acoustic and environmental data have been applied in an acoustic normal mode-based inversion approach. The dispersion characteristics of normal modes are used to define the cost function of this inverse problem. The inverted results indicate that the proposed approach with a dimension-reduced parameter space can provide a more effective way to obtain reliable estimates compared to conventional full field inversion methods. This research is supported by the U.S. Navy Office of Naval Research.



Dr. Wan received the double B.S. degrees with honor in Mechanical Engineering and Electrical & Electronics Engineering, and the M.S. degree in Underwater Acoustics from Shanghai Jiao Tong University (SJTU), Shanghai, China. He received the M.S. degree in Industrial Engineering and the Ph.D. degree in Mechanical Engineering from the Georgia Institute of Technology (Georgia Tech), Atlanta, GA, USA. During his Ph.D. study, he was a U.S. Navy Office of Naval Research (ONR) Graduate Traineeship Awardee. Then he worked as a Postdoctoral Fellow at the School of Mechanical Engineering, Georgia Tech. After his postdoctoral research at Georgia Tech, he joined the Ocean Acoustics Laboratory at the University of Delaware, Newark, DE, USA, where he is currently a Research Associate III in the Electrical and Computer Engineering Department.

Dr. Wan has been conducting experimental and theoretical research in ocean acoustics, acoustical oceanography, and acoustic signal processing. He has participated in five ONR-sponsored major shallow water acoustic experiments since 2006 (77 days at sea). His research interests include geo-acoustic inversion, internal wave effects on three-dimensional sound propagation, Arctic acoustics, acoustic array design, and time-frequency analysis of broadband signals. His research has been supported by two research grants from ONR.

Dr. Wan is a member of the Acoustical Society of America (ASA). He has served as a session chair for ASA meetings. He has received an Early Career Travel Grant, the Best Student Paper Award in Underwater Acoustics, and the Best Student Paper Award in Acoustical Oceanography from ASA. He has achieved several other awards, including a Special Research Award from ONR Ocean Acoustics Program, and the Woodruff Fellowship from Georgia Tech.  Dr. Wan is currently an editorial board member for the Springer's Journal of Marine Science and Application. He has served as a technical committee member for international conferences and a reviewer for seven refereed journals.

Monday, April 22, 2019 at 11:15am to 12:05pm

Evans Hall, Evans 204
Evans Hall, University of Delaware, Newark, DE 19716, USA

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Students, Academics, Faculty & Staff, College of Engineering, Community, Lectures and Programs



Electrical and Computer Engineering



ENGR - Electrical & Computer Engineering
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