Combined Multilateration with Machine Learning for Enhanced Aircraft Localization
In this paper, we present an aircraft localization solution developed in the context of the Aircraft Localization Competition and applied to the OpenSky Network real-world ADS-B data. The developed solution is based on a combination of machine learning and multilateration using data provided by time...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-12-01
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| Series: | Proceedings |
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| Online Access: | https://www.mdpi.com/2504-3900/59/1/2 |
| _version_ | 1826994390153822208 |
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| author | Benoit Figuet Raphael Monstein Michael Felux |
| author_facet | Benoit Figuet Raphael Monstein Michael Felux |
| author_sort | Benoit Figuet |
| collection | DOAJ |
| description | In this paper, we present an aircraft localization solution developed in the context of the Aircraft Localization Competition and applied to the OpenSky Network real-world ADS-B data. The developed solution is based on a combination of machine learning and multilateration using data provided by time synchronized ground receivers. A gradient boosting regression technique is used to obtain an estimate of the geometric altitude of the aircraft, as well as a first guess of the 2D aircraft position. Then, a triplet-wise and an all-in-view multilateration technique are implemented to obtain an accurate estimate of the aircraft latitude and longitude. A sensitivity analysis of the accuracy as a function of the number of receivers is conducted and used to optimize the proposed solution. The obtained predictions have an accuracy below 25 m for the 2D root mean squared error and below 35 m for the geometric altitude. |
| first_indexed | 2024-03-10T14:25:17Z |
| format | Article |
| id | doaj.art-773b2fde364844638a370a4fadd5c2fd |
| institution | Directory Open Access Journal |
| issn | 2504-3900 |
| language | English |
| last_indexed | 2025-02-18T09:17:58Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Proceedings |
| spelling | doaj.art-773b2fde364844638a370a4fadd5c2fd2024-11-02T22:15:11ZengMDPI AGProceedings2504-39002020-12-01591210.3390/proceedings2020059002Combined Multilateration with Machine Learning for Enhanced Aircraft LocalizationBenoit Figuet0Raphael Monstein1Michael Felux2Centre for Aviation, School of Engineering, Zurich University of Applied Sciences, 8400 Winterthur, SwitzerlandCentre for Aviation, School of Engineering, Zurich University of Applied Sciences, 8400 Winterthur, SwitzerlandCentre for Aviation, School of Engineering, Zurich University of Applied Sciences, 8400 Winterthur, SwitzerlandIn this paper, we present an aircraft localization solution developed in the context of the Aircraft Localization Competition and applied to the OpenSky Network real-world ADS-B data. The developed solution is based on a combination of machine learning and multilateration using data provided by time synchronized ground receivers. A gradient boosting regression technique is used to obtain an estimate of the geometric altitude of the aircraft, as well as a first guess of the 2D aircraft position. Then, a triplet-wise and an all-in-view multilateration technique are implemented to obtain an accurate estimate of the aircraft latitude and longitude. A sensitivity analysis of the accuracy as a function of the number of receivers is conducted and used to optimize the proposed solution. The obtained predictions have an accuracy below 25 m for the 2D root mean squared error and below 35 m for the geometric altitude.https://www.mdpi.com/2504-3900/59/1/2OpenSky NetworkADS-Blocalizationmultilaterationmachine learning |
| spellingShingle | Benoit Figuet Raphael Monstein Michael Felux Combined Multilateration with Machine Learning for Enhanced Aircraft Localization Proceedings OpenSky Network ADS-B localization multilateration machine learning |
| title | Combined Multilateration with Machine Learning for Enhanced Aircraft Localization |
| title_full | Combined Multilateration with Machine Learning for Enhanced Aircraft Localization |
| title_fullStr | Combined Multilateration with Machine Learning for Enhanced Aircraft Localization |
| title_full_unstemmed | Combined Multilateration with Machine Learning for Enhanced Aircraft Localization |
| title_short | Combined Multilateration with Machine Learning for Enhanced Aircraft Localization |
| title_sort | combined multilateration with machine learning for enhanced aircraft localization |
| topic | OpenSky Network ADS-B localization multilateration machine learning |
| url | https://www.mdpi.com/2504-3900/59/1/2 |
| work_keys_str_mv | AT benoitfiguet combinedmultilaterationwithmachinelearningforenhancedaircraftlocalization AT raphaelmonstein combinedmultilaterationwithmachinelearningforenhancedaircraftlocalization AT michaelfelux combinedmultilaterationwithmachinelearningforenhancedaircraftlocalization |