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NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models
Blue force tracking represents an essential task in the field of military applications. A blue force tracking system provides the location information of their own forces on a map to commanders. For the command post, this results in more efficient operation control with increasing safety. In undergr...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028065/ https://www.ncbi.nlm.nih.gov/pubmed/35458967 http://dx.doi.org/10.3390/s22082982 |
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author | Mascher, Karin Watzko, Markus Koppert, Axel Eder, Julian Hofer, Peter Wieser, Manfred |
author_facet | Mascher, Karin Watzko, Markus Koppert, Axel Eder, Julian Hofer, Peter Wieser, Manfred |
author_sort | Mascher, Karin |
collection | PubMed |
description | Blue force tracking represents an essential task in the field of military applications. A blue force tracking system provides the location information of their own forces on a map to commanders. For the command post, this results in more efficient operation control with increasing safety. In underground structures (e.g., tunnels or subways), the localisation is challenging due to the lack of GNSS signals. This paper presents a localisation system for military or emergency forces tailored to usage in complex underground structures. In a particle filter, position changes from a dual foot-mounted INS are fused with opportunistic UWB ranges and data from a 3D tunnel model to derive position information. A concept to deal with the absence of UWB infrastructure or 3D tunnel models is illustrated. Recurrent neural network methodologies are applied to cope with different motion types of the operators. The evaluation of the positioning algorithm took place in a street tunnel. If a fully installed infrastructure was available, positioning errors under one metre were reached. The results also showed that the INS can bridge UWB outages. A particle-filter-based approach to UWB anchor mapping is presented, and the first simulation results showed its viability. |
format | Online Article Text |
id | pubmed-9028065 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90280652022-04-23 NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models Mascher, Karin Watzko, Markus Koppert, Axel Eder, Julian Hofer, Peter Wieser, Manfred Sensors (Basel) Article Blue force tracking represents an essential task in the field of military applications. A blue force tracking system provides the location information of their own forces on a map to commanders. For the command post, this results in more efficient operation control with increasing safety. In underground structures (e.g., tunnels or subways), the localisation is challenging due to the lack of GNSS signals. This paper presents a localisation system for military or emergency forces tailored to usage in complex underground structures. In a particle filter, position changes from a dual foot-mounted INS are fused with opportunistic UWB ranges and data from a 3D tunnel model to derive position information. A concept to deal with the absence of UWB infrastructure or 3D tunnel models is illustrated. Recurrent neural network methodologies are applied to cope with different motion types of the operators. The evaluation of the positioning algorithm took place in a street tunnel. If a fully installed infrastructure was available, positioning errors under one metre were reached. The results also showed that the INS can bridge UWB outages. A particle-filter-based approach to UWB anchor mapping is presented, and the first simulation results showed its viability. MDPI 2022-04-13 /pmc/articles/PMC9028065/ /pubmed/35458967 http://dx.doi.org/10.3390/s22082982 Text en © 2022 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 Mascher, Karin Watzko, Markus Koppert, Axel Eder, Julian Hofer, Peter Wieser, Manfred NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title | NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title_full | NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title_fullStr | NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title_full_unstemmed | NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title_short | NIKE BLUETRACK: Blue Force Tracking in GNSS-Denied Environments Based on the Fusion of UWB, IMUs and 3D Models |
title_sort | nike bluetrack: blue force tracking in gnss-denied environments based on the fusion of uwb, imus and 3d models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9028065/ https://www.ncbi.nlm.nih.gov/pubmed/35458967 http://dx.doi.org/10.3390/s22082982 |
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