음선 기반 블라인드 디컨볼루션을 이용한 선박 소음으로부터의 채널 임펄스 응답 추정
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 변기훈 | - |
dc.contributor.author | 오세현 | - |
dc.contributor.author | 변성훈 | - |
dc.contributor.author | 김재수 | - |
dc.date.accessioned | 2021-12-08T13:40:14Z | - |
dc.date.available | 2021-12-08T13:40:14Z | - |
dc.date.issued | 20160602 | - |
dc.identifier.uri | https://www.kriso.re.kr/sciwatch/handle/2021.sw.kriso/3813 | - |
dc.description.abstract | The Shallow-water Acoustic Variability Experiment 2015 (SAVEX15) conducted in the Northern East China Sea (ECS) in May 2015 demonstrated that the channel impulse response can be estimated by the shipping noise using ray-based synthetic time reversal (STR) method (S. H. Byun and K. G. Sabra, 2016). Ray-based synthetic time reversal (or artificial time reversal) is a technique for blind deconvolution which determines the impulse response from the received signals when the source signal and the environment’s impulse response are both unknown (S. H. Abadi et al. 2012). The experiment utilized a vertical line array (VLA) of 16 elements spanning 56.25 m of a 100-m water column. This paper describes how ray-based STR can be exploited for the channel impulse response estimation from a variety of the shipping noise data with a bandwidth of 200 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | 음선 기반 블라인드 디컨볼루션을 이용한 선박 소음으로부터의 채널 임펄스 응답 추정 | - |
dc.title.alternative | An estimation of channel impulse response from shipping noise using ray-based blind deconvolution | - |
dc.type | Conference | - |
dc.citation.title | SAVEX15 워크샵 | - |
dc.citation.volume | 1 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 13 | - |
dc.citation.endPage | 13 | - |
dc.citation.conferenceName | SAVEX15 워크샵 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(34103) 대전광역시 유성구 유성대로1312번길 32042-866-3114
COPYRIGHT 2021 BY KOREA RESEARCH INSTITUTE OF SHIPS & OCEAN ENGINEERING. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.