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Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)

Aquatic positional telemetry offers vast opportunities to study in vivo behaviour of wild animals, but there is room for improvement in the data quality provided by current procedures for estimating positions. Here we present a novel positioning method called YAPS (Yet Another Positioning Solver), i...

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Autores principales: Baktoft, Henrik, Gjelland, Karl Øystein, Økland, Finn, Thygesen, Uffe Høgsbro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662720/
https://www.ncbi.nlm.nih.gov/pubmed/29084968
http://dx.doi.org/10.1038/s41598-017-14278-z
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author Baktoft, Henrik
Gjelland, Karl Øystein
Økland, Finn
Thygesen, Uffe Høgsbro
author_facet Baktoft, Henrik
Gjelland, Karl Øystein
Økland, Finn
Thygesen, Uffe Høgsbro
author_sort Baktoft, Henrik
collection PubMed
description Aquatic positional telemetry offers vast opportunities to study in vivo behaviour of wild animals, but there is room for improvement in the data quality provided by current procedures for estimating positions. Here we present a novel positioning method called YAPS (Yet Another Positioning Solver), involving Maximum Likelihood analysis of a state-space model applied directly to time of arrival (TOA) data in combination with a movement model. YAPS avoids the sequential positioning-filtering-approach applied in alternative tools by using all available data in a single model, and offers better accuracy and error control. Feasibility and performance of YAPS was rigorously tested in a simulation study and by applying YAPS to data from an acoustic transmitter towed in a receiver array. Performance was compared to an alternative positioning model and proprietary software. The simulation study and field test revealed that YAPS performance was better and more consistent than alternatives. We conclude that YAPS outperformed the compared alternative methods, and that YAPS constitute a vast improvement to currently available positioning software in acoustic telemetry. Additionally, in contrast to vendor-supplied solutions, YAPS is transparent, flexible and can easily be adapted and extended for further improvements or to meet study specific requirements such as three-dimensional positioning.
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spelling pubmed-56627202017-11-08 Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver) Baktoft, Henrik Gjelland, Karl Øystein Økland, Finn Thygesen, Uffe Høgsbro Sci Rep Article Aquatic positional telemetry offers vast opportunities to study in vivo behaviour of wild animals, but there is room for improvement in the data quality provided by current procedures for estimating positions. Here we present a novel positioning method called YAPS (Yet Another Positioning Solver), involving Maximum Likelihood analysis of a state-space model applied directly to time of arrival (TOA) data in combination with a movement model. YAPS avoids the sequential positioning-filtering-approach applied in alternative tools by using all available data in a single model, and offers better accuracy and error control. Feasibility and performance of YAPS was rigorously tested in a simulation study and by applying YAPS to data from an acoustic transmitter towed in a receiver array. Performance was compared to an alternative positioning model and proprietary software. The simulation study and field test revealed that YAPS performance was better and more consistent than alternatives. We conclude that YAPS outperformed the compared alternative methods, and that YAPS constitute a vast improvement to currently available positioning software in acoustic telemetry. Additionally, in contrast to vendor-supplied solutions, YAPS is transparent, flexible and can easily be adapted and extended for further improvements or to meet study specific requirements such as three-dimensional positioning. Nature Publishing Group UK 2017-10-30 /pmc/articles/PMC5662720/ /pubmed/29084968 http://dx.doi.org/10.1038/s41598-017-14278-z Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Baktoft, Henrik
Gjelland, Karl Øystein
Økland, Finn
Thygesen, Uffe Høgsbro
Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title_full Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title_fullStr Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title_full_unstemmed Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title_short Positioning of aquatic animals based on time-of-arrival and random walk models using YAPS (Yet Another Positioning Solver)
title_sort positioning of aquatic animals based on time-of-arrival and random walk models using yaps (yet another positioning solver)
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5662720/
https://www.ncbi.nlm.nih.gov/pubmed/29084968
http://dx.doi.org/10.1038/s41598-017-14278-z
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