Detecting Outlier Positions in Publicly Available ADS-B Data Sets

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F24%3A00376524" target="_blank" >RIV/68407700:21260/24:00376524 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.23919/NTCA60572.2024.10517858" target="_blank" >https://doi.org/10.23919/NTCA60572.2024.10517858</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.23919/NTCA60572.2024.10517858" target="_blank" >10.23919/NTCA60572.2024.10517858</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Detecting Outlier Positions in Publicly Available ADS-B Data Sets

Popis výsledku v původním jazyce

Automatic Dependent Surveillance - Broadcast (ADS-B) is one of the most widely used surveillance technologies in aviation. The data from ADS-Bare extensively used for commercial and research purposes. Incorrect positional messages present in the data could lead to wrong or misleading scientific conclusions. The paper presents two different methods for ADS-B position outlier detection. First, the use of Density Based Spatial Clustering of Applications with Noise algorithm is proposed. Second, the use of the Interacting Multiple Model algorithm is proposed, where the statistical distribution of the innovation is as a means for outlier detection. Both algorithms are compared on a large publicly available data set consisting of 513 million messages. The advantages and disadvantages of both of the algorithms are discussed and recommendations for their use are provided. The results indicate that up to 0.75 % of ADS-B Airborne Position Messages should be discarded.

Název v anglickém jazyce

Detecting Outlier Positions in Publicly Available ADS-B Data Sets

Popis výsledku anglicky

Automatic Dependent Surveillance - Broadcast (ADS-B) is one of the most widely used surveillance technologies in aviation. The data from ADS-Bare extensively used for commercial and research purposes. Incorrect positional messages present in the data could lead to wrong or misleading scientific conclusions. The paper presents two different methods for ADS-B position outlier detection. First, the use of Density Based Spatial Clustering of Applications with Noise algorithm is proposed. Second, the use of the Interacting Multiple Model algorithm is proposed, where the statistical distribution of the innovation is as a means for outlier detection. Both algorithms are compared on a large publicly available data set consisting of 513 million messages. The advantages and disadvantages of both of the algorithms are discussed and recommendations for their use are provided. The results indicate that up to 0.75 % of ADS-B Airborne Position Messages should be discarded.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

New Trends in Civil Aviation: Proceedings of the 24th International Conference on New Trends in Civil Aviation 2024

ISBN

978-80-01-07181-6

ISSN

2694-7854

e-ISSN

—

Počet stran výsledku

7

Strana od-do

19-25

Název nakladatele

České vysoké učení technické v Praze

Místo vydání

Praha

Místo konání akce

Praha

Datum konání akce

25. 4. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001223424800043