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...
Autores principales: | , , , , , , , , , |
---|---|
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 |