Self-localization of a deforming swarm of underwater vehicles using impulsive sound sources of opportunity

TitleSelf-localization of a deforming swarm of underwater vehicles using impulsive sound sources of opportunity
Publication TypeJournal Article
Year of Publication2018
AuthorsNaughton P., Roux P, Schurgers C., Kastner R., Jaffe J.S, Roberts P.LD
Volume6
Pagination1635-1646
Date Published2018/03
Type of ArticleArticle
ISBN Number2169-3536
Accession NumberWOS:000425686800021
Keywordsalgorithms; ambient noise; ambient noise correlations; array; calibration; coherent wave-fronts; Computer Science; cross-correlation; emergence rate; Engineering; greens-function; navigation system; ocean; self-localization; Telecommunications; underwater; underwater acoustics; vehicles
Abstract

There is increasing interest in deploying swarms of underwater vehicles for marine surveys. One of the main challenges when designing these systems is coming up with an appropriate way to localize each vehicle in relation to one another. This paper considers the self-localization of a deforming swarm of subsurface floating vehicles using impulsive sources of opportunity, such as the sounds of snapping shrimp that are present in warm coastal waters. Impulsive sound sources provide high intensity, broadband signals that facilitate accurate arrival time detections across each vehicle. This makes them useful references for a self-localization solution. However, the similarity between different signals presents a significant correspondence problem, which must be solved to provide accurate estimates of the changing geometry of the swarm. A geometric solution to this correspondence problem is shown and an optimization procedure is proposed to track the geometry of a swarm as it changes. The method is verified using a swarm of 17 self-ballasting subsurface floats that independently drifted with currents off of the coast of San Diego, California. The changing geometry of the floats was estimated using both an acoustic localization system and the proposed approach. The two estimates show good agreement, validating our method. We believe that this new localization strategy is useful for high endurance, low power, and multi-vehicle surveys.

DOI10.1109/access.2017.2779835
Student Publication: 
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