Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques
This paper presents significant enhancements to the vertical reconstruction component of EUROCONTROL’s Surveillance Analysis Support System for ATC Centres (SASS-C). We introduce four key improvements: (1) a novel segmentation algorithm for more precise flight phase identification, (2) an improved i...
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| Format: | Article |
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MDPI AG
2024-10-01
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| Series: | Aerospace |
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| Online Access: | https://www.mdpi.com/2226-4310/11/11/900 |
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| author | Daniel Amigo David Sánchez Pedroche Jesús García José Manuel Molina Jekaterina Trofimova Emmanuel Voet Benoît Van Bogaert |
| author_facet | Daniel Amigo David Sánchez Pedroche Jesús García José Manuel Molina Jekaterina Trofimova Emmanuel Voet Benoît Van Bogaert |
| author_sort | Daniel Amigo |
| collection | DOAJ |
| description | This paper presents significant enhancements to the vertical reconstruction component of EUROCONTROL’s Surveillance Analysis Support System for ATC Centres (SASS-C). We introduce four key improvements: (1) a novel segmentation algorithm for more precise flight phase identification, (2) an improved invalid height detection process using LOWESS and sliding window analysis, (3) a protection mechanism against simultaneous measurements at the Kalman filter level, and (4) an optimized approach for smooth overshoot correction during segment transitions. These advancements address limitations in the current system, particularly in trajectory segmentation accuracy and robustness against measurement anomalies. Our methodology employs both synthetic and real-world data for comprehensive evaluation, ensuring performance under controlled and operational conditions. The results demonstrate substantial improvements in segmentation precision, outlier detection, and overall trajectory reconstruction quality. The invalid detection algorithm, while incurring a slight computational cost, significantly enhances trajectory accuracy. These enhancements contribute to more reliable air traffic analysis, supporting safer and more efficient airspace management. The paper concludes by discussing potential future work, including the application of machine learning techniques and the extension of these improvements to horizontal reconstruction processes. |
| format | Article |
| id | doaj-art-d04532774a8f460fbb2c5d44c76072d3 |
| institution | OA Journals |
| issn | 2226-4310 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj-art-d04532774a8f460fbb2c5d44c76072d32025-08-20T02:26:50ZengMDPI AGAerospace2226-43102024-10-01111190010.3390/aerospace11110900Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering TechniquesDaniel Amigo0David Sánchez Pedroche1Jesús García2José Manuel Molina3Jekaterina Trofimova4Emmanuel Voet5Benoît Van Bogaert6Group GIAA, University Carlos III of Madrid, Avd. de Gregorio Peces-Barba Martínez, 22, 28270 Colmenarejo, SpainGroup GIAA, University Carlos III of Madrid, Avd. de Gregorio Peces-Barba Martínez, 22, 28270 Colmenarejo, SpainGroup GIAA, University Carlos III of Madrid, Avd. de Gregorio Peces-Barba Martínez, 22, 28270 Colmenarejo, SpainGroup GIAA, University Carlos III of Madrid, Avd. de Gregorio Peces-Barba Martínez, 22, 28270 Colmenarejo, SpainEuropean Organisation for the Safety of Air Navigation (EUROCONTROL), NMD/INF/CNS SASS-C, Rue de la Fusee, 96, 1130 Brussels, BelgiumEuropean Organisation for the Safety of Air Navigation (EUROCONTROL), NMD/INF/CNS SASS-C, Rue de la Fusee, 96, 1130 Brussels, BelgiumEuropean Organisation for the Safety of Air Navigation (EUROCONTROL), NMD/INF/CNS SASS-C, Rue de la Fusee, 96, 1130 Brussels, BelgiumThis paper presents significant enhancements to the vertical reconstruction component of EUROCONTROL’s Surveillance Analysis Support System for ATC Centres (SASS-C). We introduce four key improvements: (1) a novel segmentation algorithm for more precise flight phase identification, (2) an improved invalid height detection process using LOWESS and sliding window analysis, (3) a protection mechanism against simultaneous measurements at the Kalman filter level, and (4) an optimized approach for smooth overshoot correction during segment transitions. These advancements address limitations in the current system, particularly in trajectory segmentation accuracy and robustness against measurement anomalies. Our methodology employs both synthetic and real-world data for comprehensive evaluation, ensuring performance under controlled and operational conditions. The results demonstrate substantial improvements in segmentation precision, outlier detection, and overall trajectory reconstruction quality. The invalid detection algorithm, while incurring a slight computational cost, significantly enhances trajectory accuracy. These enhancements contribute to more reliable air traffic analysis, supporting safer and more efficient airspace management. The paper concludes by discussing potential future work, including the application of machine learning techniques and the extension of these improvements to horizontal reconstruction processes.https://www.mdpi.com/2226-4310/11/11/900trajectory reconstructionvertical segmentationKalman filteringoutlier detectionSASS-CEUROCONTROL |
| spellingShingle | Daniel Amigo David Sánchez Pedroche Jesús García José Manuel Molina Jekaterina Trofimova Emmanuel Voet Benoît Van Bogaert Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques Aerospace trajectory reconstruction vertical segmentation Kalman filtering outlier detection SASS-C EUROCONTROL |
| title | Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques |
| title_full | Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques |
| title_fullStr | Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques |
| title_full_unstemmed | Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques |
| title_short | Enhancing Vertical Trajectory Reconstruction in SASS-C: Advanced Segmentation, Outlier Detection, and Filtering Techniques |
| title_sort | enhancing vertical trajectory reconstruction in sass c advanced segmentation outlier detection and filtering techniques |
| topic | trajectory reconstruction vertical segmentation Kalman filtering outlier detection SASS-C EUROCONTROL |
| url | https://www.mdpi.com/2226-4310/11/11/900 |
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