Alfie Anthony Treloar;Hugh Maclean;Jan Bujalka;Jon Narramore;Ben Thomas;Philippe Blondel;Alan Hunter
{"title":"Real-Time In-Situ Passive Acoustic Array Beamforming From the AutoNaut Wave-Propelled Uncrewed Surface Vessel","authors":"Alfie Anthony Treloar;Hugh Maclean;Jan Bujalka;Jon Narramore;Ben Thomas;Philippe Blondel;Alan Hunter","doi":"10.1109/JOE.2024.3365169","DOIUrl":null,"url":null,"abstract":"This article presents the first demonstration of beamforming, detection, and bearing estimation of an underwater acoustic source from an eight-element thin line hydrophone array towed behind the AutoNaut wave-propelled uncrewed surface vessel. This has been achieved in situ and in real time during an experimental sea trial off the coast of Plymouth, U.K. A controlled acoustic source was towed from a support vessel while emitting seven tonals with frequencies between 480–1630 Hz and source levels between 93–126 dB. This allowed the detection performance of the array to be assessed and demonstrated for an acoustic source with known bearing and range. In postprocessing, the shape of the array was estimated using a cubic spline model, exploiting measurements from pressure and three-axis compass sensors integrated at each end of the array. The beamforming was repeated using the estimated array shape to infer the hydrophone positions, which resulted in a median improvement of 0.38 dB and maximum of 5.8 dB in the MUSIC beamforming output, and a potential reduction in the left/right bearing estimation ambiguities. The outcomes of this work demonstrate that the AutoNaut is an effective platform for towed array passive acoustic monitoring.","PeriodicalId":13191,"journal":{"name":"IEEE Journal of Oceanic Engineering","volume":"49 3","pages":"713-726"},"PeriodicalIF":3.8000,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Oceanic Engineering","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10496484/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
This article presents the first demonstration of beamforming, detection, and bearing estimation of an underwater acoustic source from an eight-element thin line hydrophone array towed behind the AutoNaut wave-propelled uncrewed surface vessel. This has been achieved in situ and in real time during an experimental sea trial off the coast of Plymouth, U.K. A controlled acoustic source was towed from a support vessel while emitting seven tonals with frequencies between 480–1630 Hz and source levels between 93–126 dB. This allowed the detection performance of the array to be assessed and demonstrated for an acoustic source with known bearing and range. In postprocessing, the shape of the array was estimated using a cubic spline model, exploiting measurements from pressure and three-axis compass sensors integrated at each end of the array. The beamforming was repeated using the estimated array shape to infer the hydrophone positions, which resulted in a median improvement of 0.38 dB and maximum of 5.8 dB in the MUSIC beamforming output, and a potential reduction in the left/right bearing estimation ambiguities. The outcomes of this work demonstrate that the AutoNaut is an effective platform for towed array passive acoustic monitoring.
期刊介绍:
The IEEE Journal of Oceanic Engineering (ISSN 0364-9059) is the online-only quarterly publication of the IEEE Oceanic Engineering Society (IEEE OES). The scope of the Journal is the field of interest of the IEEE OES, which encompasses all aspects of science, engineering, and technology that address research, development, and operations pertaining to all bodies of water. This includes the creation of new capabilities and technologies from concept design through prototypes, testing, and operational systems to sense, explore, understand, develop, use, and responsibly manage natural resources.