Cargando…

Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions

Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the performance of such systems is a simulation approach to...

Descripción completa

Detalles Bibliográficos
Autores principales: Jain, Aishvarya Kumar, Schott, Dominik Jan, Scheithauer, Hermann, Häring, Ivo, Höflinger, Fabian, Fischer, Georg, Habets, Emanuël A. P., Gelhausen, Patrick, Schindelhauer, Christian, Rupitsch, Stefan Johann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512807/
https://www.ncbi.nlm.nih.gov/pubmed/34640652
http://dx.doi.org/10.3390/s21196332
_version_ 1784583085233274880
author Jain, Aishvarya Kumar
Schott, Dominik Jan
Scheithauer, Hermann
Häring, Ivo
Höflinger, Fabian
Fischer, Georg
Habets, Emanuël A. P.
Gelhausen, Patrick
Schindelhauer, Christian
Rupitsch, Stefan Johann
author_facet Jain, Aishvarya Kumar
Schott, Dominik Jan
Scheithauer, Hermann
Häring, Ivo
Höflinger, Fabian
Fischer, Georg
Habets, Emanuël A. P.
Gelhausen, Patrick
Schindelhauer, Christian
Rupitsch, Stefan Johann
author_sort Jain, Aishvarya Kumar
collection PubMed
description Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the performance of such systems is a simulation approach to test their robustness in the presence of disruptions. This approach cannot only replace experiments in early phases of development but could also be used to study susceptibility, robustness, response, and recovery in case of disruptions. The paper presents a simulation framework for a TDOA-based indoor ultrasound localization system and ways to introduce different types of disruptions. This framework can be used to test the performance of TDOA-based localization algorithms in the presence of disruptions. Resilience quantification results are presented for representative disruptions. Based on these quantities, it is found that localization with arc-tangent cost function is approximately 30% more resilient than the linear cost function. The simulation approach is shown to apply to resilience engineering and can be used to increase the efficiency and quality of indoor localization methods.
format Online
Article
Text
id pubmed-8512807
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-85128072021-10-14 Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions Jain, Aishvarya Kumar Schott, Dominik Jan Scheithauer, Hermann Häring, Ivo Höflinger, Fabian Fischer, Georg Habets, Emanuël A. P. Gelhausen, Patrick Schindelhauer, Christian Rupitsch, Stefan Johann Sensors (Basel) Article Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the performance of such systems is a simulation approach to test their robustness in the presence of disruptions. This approach cannot only replace experiments in early phases of development but could also be used to study susceptibility, robustness, response, and recovery in case of disruptions. The paper presents a simulation framework for a TDOA-based indoor ultrasound localization system and ways to introduce different types of disruptions. This framework can be used to test the performance of TDOA-based localization algorithms in the presence of disruptions. Resilience quantification results are presented for representative disruptions. Based on these quantities, it is found that localization with arc-tangent cost function is approximately 30% more resilient than the linear cost function. The simulation approach is shown to apply to resilience engineering and can be used to increase the efficiency and quality of indoor localization methods. MDPI 2021-09-22 /pmc/articles/PMC8512807/ /pubmed/34640652 http://dx.doi.org/10.3390/s21196332 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Jain, Aishvarya Kumar
Schott, Dominik Jan
Scheithauer, Hermann
Häring, Ivo
Höflinger, Fabian
Fischer, Georg
Habets, Emanuël A. P.
Gelhausen, Patrick
Schindelhauer, Christian
Rupitsch, Stefan Johann
Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title_full Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title_fullStr Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title_full_unstemmed Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title_short Simulation-Based Resilience Quantification of an Indoor Ultrasound Localization System in the Presence of Disruptions
title_sort simulation-based resilience quantification of an indoor ultrasound localization system in the presence of disruptions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8512807/
https://www.ncbi.nlm.nih.gov/pubmed/34640652
http://dx.doi.org/10.3390/s21196332
work_keys_str_mv AT jainaishvaryakumar simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT schottdominikjan simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT scheithauerhermann simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT haringivo simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT hoflingerfabian simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT fischergeorg simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT habetsemanuelap simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT gelhausenpatrick simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT schindelhauerchristian simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions
AT rupitschstefanjohann simulationbasedresiliencequantificationofanindoorultrasoundlocalizationsysteminthepresenceofdisruptions