Abstract
A large quantity of Mode S data is being gathered by the OpenSky receiver network every day. Information regarding common flight states, such as position, ground speed, and the vertical rate is broadcast by ADS-B and has already been decoded and made available for researchers via the OpenSky historical database. However, there is still a large amount of Mode S communication data that has not yet been fully explored. Specifically, the information contained in Enhanced Mode S Surveillance downlink messages can be utilized to better support ATM research. The challenge of decoding such information lies in the implicit inference process for Mode S Comm-B messages. This paper presents a new open library, pymodes-opensky, which connects the existing open-source pyModeS decoder to the raw Mode S messages from the OpenSky historical database through the Impala shell. It also presents a convenient workflow that can be used to obtain additional information regarding airspeeds, flight intentions, and meteorological conditions of a given flight from the OpenSky database. An analysis based on a global dataset from OpenSky is conducted, and the associated Mode S interrogation statistics in different regions are shown.
Original language | English |
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Title of host publication | Proceedings of the 7th OpenSky Workshop 2019 |
Editors | Christina Pöpper, Martin Strohmeier |
Pages | 63-72 |
Number of pages | 10 |
Volume | 67 |
DOIs | |
Publication status | Published - 2019 |
Event | 7th OpenSky Workshop 2019 - Zurich, Switzerland Duration: 21 Nov 2019 → 22 Nov 2019 Conference number: 7 |
Publication series
Name | EPiC Series in Computing |
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Workshop
Workshop | 7th OpenSky Workshop 2019 |
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Country/Territory | Switzerland |
City | Zurich |
Period | 21/11/19 → 22/11/19 |