Filtering Techniques for ADS-B Trajectory Preprocessing

This paper addresses the issue of noisy, uncertain and quantized data in crowdsourced ADS-B and Mode S data and explores propositions of implementations of preprocessing techniques to address them. After a description of ADS-B data focused on sources of noise and uncertainty, we present in detail a selection of filters that have been implemented in the traffic library, and widely used in the constitution of open datasets used in further research. We also illustrate the results of the filtering with trajectory data collected by The OpenSky Network and by inexpensive RTL-SDR receivers.

Authors

Publication Details

Journal
Journal of Open Aviation Science
Published
2025-03-20
DOI
https://doi.org/10.59490/joas.2024.7882
Citations
3
Primary Topic
Software Reliability and Analysis Research
Type
article
Field-Weighted Citation Impact
6.92
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article

Filtering Techniques for ADS-B Trajectory Preprocessing

Benoit Figuet, Xavier Olivé, Richard Alligier, Jan Krummen
3 citations
Journal of Open Aviation Science
Software Reliability and Analysis Research
6.92
article

Filtering Techniques for ADS-B Trajectory Preprocessing

Benoit Figuet, Xavier Olivé, Richard Alligier, Jan Krummen
article en
3 citations

Abstract

This paper addresses the issue of noisy, uncertain and quantized data in crowdsourced ADS-B and Mode S data and explores propositions of implementations of preprocessing techniques to address them. After a description of ADS-B data focused on sources of noise and uncertainty, we present in detail a selection of filters that have been implemented in the traffic library, and widely used in the constitution of open datasets used in further research. We also illustrate the results of the filtering with trajectory data collected by The OpenSky Network and by inexpensive RTL-SDR receivers.

Journal of Open Aviation ScienceVol. 2(2)
Openalex Percentile: Top 4%
Software Reliability and Analysis Research
6.92
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