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Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm

Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace...

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Detalles Bibliográficos
Autores principales: Mao, Yi, Yang, Yi, Hu, Yuxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891308/
https://www.ncbi.nlm.nih.gov/pubmed/31731631
http://dx.doi.org/10.3390/s19224975
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author Mao, Yi
Yang, Yi
Hu, Yuxin
author_facet Mao, Yi
Yang, Yi
Hu, Yuxin
author_sort Mao, Yi
collection PubMed
description Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration.
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spelling pubmed-68913082019-12-12 Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm Mao, Yi Yang, Yi Hu, Yuxin Sensors (Basel) Article Targeted information sources include radar and ADS (Automatic Dependent Surveillance) for civil ATM (Air Traffic Management) systems, and the new navigation system based on satellites has the capability of global coverage. In order to solve the surveillance problem in mid-and-high altitude airspace and approaching airspace, this paper proposes a filter-based covariance matrix weighting method, measurement variance weighting method, and measurement-first weighted fusion method weighting integration algorithm to improve the efficiency of data integration calculation under fixed accuracy. Besides this, this paper focuses on the technology of the integration of a multi-radar surveillance system and automated related surveillance system in the ATM system and analyzes the constructional method of a multigeneration surveillance data integration system, as well as establishing the targeted model of sensors and the target track and designing the logical structure of multi-radar and ADS data integration. MDPI 2019-11-15 /pmc/articles/PMC6891308/ /pubmed/31731631 http://dx.doi.org/10.3390/s19224975 Text en © 2019 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Mao, Yi
Yang, Yi
Hu, Yuxin
Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title_full Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title_fullStr Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title_full_unstemmed Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title_short Research into a Multi-Variate Surveillance Data Fusion Processing Algorithm
title_sort research into a multi-variate surveillance data fusion processing algorithm
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6891308/
https://www.ncbi.nlm.nih.gov/pubmed/31731631
http://dx.doi.org/10.3390/s19224975
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