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Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management
Unmanned traffic management (UTM) systems rely on collaborative position reporting to track unmanned aerial system (UAS) operations over wide unsurveilled (with counter-UAS systems) areas. Many different technologies, such as Remote-ID, ADS-B, FLARM, or MLAT might be used for this purpose, in additi...
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/PMC8877271/ https://www.ncbi.nlm.nih.gov/pubmed/35214400 http://dx.doi.org/10.3390/s22041498 |
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author | Besada, Juan A. Carramiñana, David Bergesio, Luca Campaña, Ivan Bernardos, Ana M. |
author_facet | Besada, Juan A. Carramiñana, David Bergesio, Luca Campaña, Ivan Bernardos, Ana M. |
author_sort | Besada, Juan A. |
collection | PubMed |
description | Unmanned traffic management (UTM) systems rely on collaborative position reporting to track unmanned aerial system (UAS) operations over wide unsurveilled (with counter-UAS systems) areas. Many different technologies, such as Remote-ID, ADS-B, FLARM, or MLAT might be used for this purpose, in addition to the direct exploitation of C2 telemetry, relayed though cellular networks. This paper provides an overview of the most used collaborative sensors and surveillance systems in this context, analyzing their main technical parameters and performance effects. In addition, this paper proposes an abstracted general statistical simulation model covering message encoding, network capacity and access, sensors coverage and distribution, message transmission and decoding. Making use of this abstracted model, this paper proposes a particularized set of simulation models for ADS-B, FLARM and Remote-Id; it is thus useful to test their potential integration in UTM systems. Finally, a comparative analysis, based on simulation, of these systems, is performed. It is shown that the most relevant effects are those related with quantification and the potential saturation of the communication channels leading to collisions and delays. |
format | Online Article Text |
id | pubmed-8877271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88772712022-02-26 Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management Besada, Juan A. Carramiñana, David Bergesio, Luca Campaña, Ivan Bernardos, Ana M. Sensors (Basel) Article Unmanned traffic management (UTM) systems rely on collaborative position reporting to track unmanned aerial system (UAS) operations over wide unsurveilled (with counter-UAS systems) areas. Many different technologies, such as Remote-ID, ADS-B, FLARM, or MLAT might be used for this purpose, in addition to the direct exploitation of C2 telemetry, relayed though cellular networks. This paper provides an overview of the most used collaborative sensors and surveillance systems in this context, analyzing their main technical parameters and performance effects. In addition, this paper proposes an abstracted general statistical simulation model covering message encoding, network capacity and access, sensors coverage and distribution, message transmission and decoding. Making use of this abstracted model, this paper proposes a particularized set of simulation models for ADS-B, FLARM and Remote-Id; it is thus useful to test their potential integration in UTM systems. Finally, a comparative analysis, based on simulation, of these systems, is performed. It is shown that the most relevant effects are those related with quantification and the potential saturation of the communication channels leading to collisions and delays. MDPI 2022-02-15 /pmc/articles/PMC8877271/ /pubmed/35214400 http://dx.doi.org/10.3390/s22041498 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 Besada, Juan A. Carramiñana, David Bergesio, Luca Campaña, Ivan Bernardos, Ana M. Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title | Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title_full | Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title_fullStr | Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title_full_unstemmed | Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title_short | Modelling and Simulation of Collaborative Surveillance for Unmanned Traffic Management |
title_sort | modelling and simulation of collaborative surveillance for unmanned traffic management |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877271/ https://www.ncbi.nlm.nih.gov/pubmed/35214400 http://dx.doi.org/10.3390/s22041498 |
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