Weather field reconstruction using aircraft surveillance data and a novel meteo-particle model

Wind and temperature data are important parameters in aircraft performance studies. The lack of accurate measurements of these parameters forces researchers to rely on numerical weather prediction models, which are often filtered for a larger area with decreased local accuracy. Aircraft, however, also transmit information related to weather...

Modeling aircraft performance parameters with open ADS-B data

Open access to flight data from ADS-B (Automatic Dependent Surveillance Broadcast) has provided researchers more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters....

Flight Extraction and Phase Identification for Large Automatic Dependent Surveillance–Broadcast Datasets

AUTOMATIC dependent surveillance–broadcast (ADS-B) [1,2] is widely implemented in modern commercial aircraft and will become mandatory equipment in 2020. Flight state information such as position, velocity, and vertical rate are broadcast by tens of thousands of aircraft around the world constantly using onboard ADS-B transponders. These data...

Modeling aircraft performance parameters with open ADS-B data

Open access to flight data from ADS-B (Automatic Dependent Surveillance Broadcast) has provided researchers more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters....

Large-Scale ADS-B Data and Signal Quality Analysis

To investigate the contradicting findings of previous studies that investigated ADS-B quality, a study was per-formed to analyze the data and signal quality of ADS-B. For this study, a large dataset of raw ADS-B messages was analyzed, regarding the quality of the data and the signal, differentiating between internal and external sources of...

Bayesian Inference of Aircraft Initial Mass

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other ATM topics. However, it is a common challenge for researchers who have no access to this proprietary information. Previously, several studies have proposed methods to estimates aircraft weight, most of which are focused on...

Ground-based Wind Field Construction from Mode-S and ADS-B Data with a Novel Gas Particle Model

Wind is an important parameter in many air traffic management researches, as it often introduces significant uncertainties in aircraft performance studies and trajectory predictions. Obtaining accurate wind field information has always been a challenge due to the availability of weather sensors. Traditionally, there is no direct method to...

Large-Scale Flight Phase Identification from ADS-B Data Using Machine Learning Methods

With the increasing availability of ADS-B transponders on commercial aircraft, as well as the rapidly growing deployment of ground stations that provide public access to their data, accessing open aircraft flight data is becoming easier for researchers. Given the large number of operational aircraft, significant amounts of flight data can be...

Modeling and Inferring Aircraft Takeoff Mass from Runway ADS-B Data

Aircraft mass is an important parameter in many ways, either to build aircraft performance models, to predict flight trajectories, or to simulate air traffic. Mass data is usually considered as sensitive information for airlines and is, therefore, not disclosed to researchers publicly. In this paper, we use two methods to infer the mass of an...