2014
DOI: 10.1109/tits.2014.2345055
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Efficient Compression of 4D-Trajectory Data in Air Traffic Management

Abstract: Air traffic management (ATM) is facing a tremendous increase in the amount of available flight data, particularly four-dimensional (4D) trajectories. Computational requirements for analysis and storage of such bulk of data are steeply increasing. Compression is one key technology to address this challenge. In this paper we propose two techniques for compressing air traffic 4D trajectories. Our first technique analyzes a set of samples and computes a prediction for the most likely picked successor coordinate by… Show more

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Cited by 14 publications
(10 citation statements)
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“…As a minimum, the input data must characterize the flight tracks and emissions in the "upper" airspace above flight level (FL) 180 (18 000 feet, about 5.5 km), where most contrails form. Previous CoCiP studies have used air traffic from various sources, including a global track database for 2006 (Wilkerson et al, 2010;Brasseur et al, 2016), data collected for the field experiment ML-CIRRUS over Europe and the North Atlantic in March and April 2014 (Schumann et al, 2016;, or traffic data for 6 weeks distributed over one year in 2012-13 in Japanese airspace (Teoh et al, 2020b). Here, all flights passing the European investigation domain are considered.…”
Section: Air Traffic and Aircraft Emissions Inputmentioning
confidence: 99%
“…As a minimum, the input data must characterize the flight tracks and emissions in the "upper" airspace above flight level (FL) 180 (18 000 feet, about 5.5 km), where most contrails form. Previous CoCiP studies have used air traffic from various sources, including a global track database for 2006 (Wilkerson et al, 2010;Brasseur et al, 2016), data collected for the field experiment ML-CIRRUS over Europe and the North Atlantic in March and April 2014 (Schumann et al, 2016;, or traffic data for 6 weeks distributed over one year in 2012-13 in Japanese airspace (Teoh et al, 2020b). Here, all flights passing the European investigation domain are considered.…”
Section: Air Traffic and Aircraft Emissions Inputmentioning
confidence: 99%
“…The CPR represents augmented surveillance position information, based on real-time surveillance data (https://www.eurocontrol.int/service/data-collection-service) derived from radar and from Automatic Dependent Surveillance -Broadcast (ADS-B) data (https://ads-b-europe.eu/). For flights outside the surveillance domain of EUROCONTROL, data from EUROCONTROL's so-called Model 3 (M3) data (Wandelt and Sun, 2015) are used, which contain partial track information from departure to destination also outside Europe. The M3 data are flight plan data partly corrected by surveillance (radar) data and are available from the DDR2 data repository of EUROCONTROL.…”
Section: Air Traffic and Aircraft Emissions Inputmentioning
confidence: 99%
“…This section provides relevant results obtained from simulations of two ecosystems. The traffic scenario used for this purpose was DDR2, 1 s06.m1 model that comprises 4D flight plans ( 23 ) . The analysed traffic was dated on 24/08/2017 within the ECAC (European Civil Aviation Conference) airspace, with the total number of 36,095 flights during the day.…”
Section: Analysis Of Simulation Resultsmentioning
confidence: 99%