Synchronizing ADS-B Data with Bayesian Filters and Smoothers for Separation Distance Calculations

This paper investigates how the calculation of sepa-ration distances from ADS-B data received by a single receiver is affected by the asynchronously sent ADS-B data from different aircraft. Therefore, unsynchronized ADS-B data containing 838 arrivals and departures recorded over one day are synchronized using an Extended Kalman Filter and Extended Rauch Tung Striebel Smoother. We calculate pairwise separation distances for all flights based on the unsynchronized and synchronized data. Finally, we compare and statistically evaluate the differences between the unsynchronized and synchronized results.

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Publication Details

Published
2025-04-08
DOI
https://doi.org/10.1109/icns65417.2025.10976776
Primary Topic
Fault Detection and Control Systems
Type
article
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article

Synchronizing ADS-B Data with Bayesian Filters and Smoothers for Separation Distance Calculations

Lukas Beller, Florian Holzapfel
Fault Detection and Control Systems
article

Synchronizing ADS-B Data with Bayesian Filters and Smoothers for Separation Distance Calculations

Lukas Beller, Florian Holzapfel
article en

Abstract

This paper investigates how the calculation of sepa-ration distances from ADS-B data received by a single receiver is affected by the asynchronously sent ADS-B data from different aircraft. Therefore, unsynchronized ADS-B data containing 838 arrivals and departures recorded over one day are synchronized using an Extended Kalman Filter and Extended Rauch Tung Striebel Smoother. We calculate pairwise separation distances for all flights based on the unsynchronized and synchronized data. Finally, we compare and statistically evaluate the differences between the unsynchronized and synchronized results.

Technical University of Munich (DE)
Openalex Percentile: Top 90%
Fault Detection and Control Systems
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