Acoustic positioning in a reflective environment: going beyond point-by-point algorithms

Abstract Background Acoustic positioning telemetry is nowadays widely used in behavioural ecology of aquatic animals. Data on the animal’s geographical location and its changes through time are used to study for instance movement patterns, habitat use and migration. The acoustic signals are detected...

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Main Authors: Jenna Vergeynst, Thomas Vanwyck, Raf Baeyens, Tom De Mulder, Ingmar Nopens, Ans Mouton, Ine Pauwels
Format: Article
Language:English
Published: BMC 2020-05-01
Series:Animal Biotelemetry
Subjects:
VPS
HPE
Online Access:http://link.springer.com/article/10.1186/s40317-020-00203-1
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spelling doaj-0e198f3321d841bfb70fced8e7e2c9a52020-11-25T03:26:35ZengBMCAnimal Biotelemetry2050-33852020-05-018111710.1186/s40317-020-00203-1Acoustic positioning in a reflective environment: going beyond point-by-point algorithmsJenna Vergeynst0Thomas Vanwyck1Raf Baeyens2Tom De Mulder3Ingmar Nopens4Ans Mouton5Ine Pauwels6Department of Data Analysis and Mathematical Modelling, Ghent UniversityDepartment of Data Analysis and Mathematical Modelling, Ghent UniversityResearch Institute for Nature and Forest (INBO)Department of Civil Engineering, Ghent UniversityDepartment of Data Analysis and Mathematical Modelling, Ghent UniversityResearch Institute for Nature and Forest (INBO)Research Institute for Nature and Forest (INBO)Abstract Background Acoustic positioning telemetry is nowadays widely used in behavioural ecology of aquatic animals. Data on the animal’s geographical location and its changes through time are used to study for instance movement patterns, habitat use and migration. The acoustic signals are detected by stand-alone receivers, allowing to collect huge amounts of data over long periods of time. However, large volumes of data might contain large errors. The traditional Time Difference of Arrival (TDOA) method used to calculate underwater positions, is a point-by-point approach: every position is calculated independently of all other positions. This method assumes that the acoustic transmissions follow a linear path. In many environments, this assumption is violated, for instance by reflections of the acoustic signal against hard surfaces, such as rock formations and concrete walls, or by diffractions around obstacles. Hence, acoustic positioning datasets usually require additional filtering. Unfortunately, the performance of the available filtering techniques is often unclear or ambiguous, especially when reflections occur. An alternative to the point-by-point approach, is a track-oriented approach, as used by YAPS (Yet Another Positioning System). This novel algorithm uses the information that is present in previous and subsequent positions, by combining a model of fish behaviour with Time of Arrival (TOA) of the signals on the receivers. In this study, we investigated the performance of two filtering techniques applied to positions provided by the Vemco Positioning System (VPS) in a highly reflective environment. We compared the unfiltered VPS positions with a standard filtering technique, making use of the Horizontal Positioning Error (HPE), and developed a new filter based on receiver cluster classification. Finally, we recalculated the positions with YAPS and compared the performance of this system to the two filtering techniques. Results The performance of the VPS system was strongly impeded by the multiple reflections occurring in this study area, but lowering the power output of transmitters can slightly attenuate this issue. None of the filtering techniques was able to compensate for reflections and to improve the positioning accuracy significantly. Only the YAPS algorithm could cope with the high level of reflectivity in this study site. Conclusions Point-by-point algorithms might fail to provide accurate fine-scale tracks in a highly reflective acoustic environment. As this study has shown, the YAPS algorithm can provide a successful alternative, even in these difficult conditions.http://link.springer.com/article/10.1186/s40317-020-00203-1VPSAcoustic positioning telemetryHPEYAPSReflective environmentMultipath
collection DOAJ
language English
format Article
sources DOAJ
author Jenna Vergeynst
Thomas Vanwyck
Raf Baeyens
Tom De Mulder
Ingmar Nopens
Ans Mouton
Ine Pauwels
spellingShingle Jenna Vergeynst
Thomas Vanwyck
Raf Baeyens
Tom De Mulder
Ingmar Nopens
Ans Mouton
Ine Pauwels
Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
Animal Biotelemetry
VPS
Acoustic positioning telemetry
HPE
YAPS
Reflective environment
Multipath
author_facet Jenna Vergeynst
Thomas Vanwyck
Raf Baeyens
Tom De Mulder
Ingmar Nopens
Ans Mouton
Ine Pauwels
author_sort Jenna Vergeynst
title Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
title_short Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
title_full Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
title_fullStr Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
title_full_unstemmed Acoustic positioning in a reflective environment: going beyond point-by-point algorithms
title_sort acoustic positioning in a reflective environment: going beyond point-by-point algorithms
publisher BMC
series Animal Biotelemetry
issn 2050-3385
publishDate 2020-05-01
description Abstract Background Acoustic positioning telemetry is nowadays widely used in behavioural ecology of aquatic animals. Data on the animal’s geographical location and its changes through time are used to study for instance movement patterns, habitat use and migration. The acoustic signals are detected by stand-alone receivers, allowing to collect huge amounts of data over long periods of time. However, large volumes of data might contain large errors. The traditional Time Difference of Arrival (TDOA) method used to calculate underwater positions, is a point-by-point approach: every position is calculated independently of all other positions. This method assumes that the acoustic transmissions follow a linear path. In many environments, this assumption is violated, for instance by reflections of the acoustic signal against hard surfaces, such as rock formations and concrete walls, or by diffractions around obstacles. Hence, acoustic positioning datasets usually require additional filtering. Unfortunately, the performance of the available filtering techniques is often unclear or ambiguous, especially when reflections occur. An alternative to the point-by-point approach, is a track-oriented approach, as used by YAPS (Yet Another Positioning System). This novel algorithm uses the information that is present in previous and subsequent positions, by combining a model of fish behaviour with Time of Arrival (TOA) of the signals on the receivers. In this study, we investigated the performance of two filtering techniques applied to positions provided by the Vemco Positioning System (VPS) in a highly reflective environment. We compared the unfiltered VPS positions with a standard filtering technique, making use of the Horizontal Positioning Error (HPE), and developed a new filter based on receiver cluster classification. Finally, we recalculated the positions with YAPS and compared the performance of this system to the two filtering techniques. Results The performance of the VPS system was strongly impeded by the multiple reflections occurring in this study area, but lowering the power output of transmitters can slightly attenuate this issue. None of the filtering techniques was able to compensate for reflections and to improve the positioning accuracy significantly. Only the YAPS algorithm could cope with the high level of reflectivity in this study site. Conclusions Point-by-point algorithms might fail to provide accurate fine-scale tracks in a highly reflective acoustic environment. As this study has shown, the YAPS algorithm can provide a successful alternative, even in these difficult conditions.
topic VPS
Acoustic positioning telemetry
HPE
YAPS
Reflective environment
Multipath
url http://link.springer.com/article/10.1186/s40317-020-00203-1
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