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....

Aircraft Mass and Thrust Estimation Using Recursive Bayesian Method

This paper focuses on estimating aircraft mass and thrust setting using a recursive Bayesian method called particle filtering. The method is based on a nonlinear state-space system derived from aircraft point-mass performance models. Using solely ADS-B and Mode-S data, flight states such as position, velocity, and wind speed are collected and...

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...

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...

Reconstructing Aircraft Turn Manoeuvres for Trajectory Analyses Using ADS-B Data

The Automatic Dependent Surveillance-Broadcast (ADS-B) data has become one of the most popular sources of data for trajectory-based ATM studies. It is can be received in most of the world without restrictions. Extended coverage can be achieved with a network of low-cost receivers and satellites. However, the fact that ADS-B is designed to...

Aircraft Drag Polar Estimation Based on a Stochastic Hierarchical Model

The aerodynamic properties of an aircraft determine a crucial part of the aircraft performance model. Deriving accurate aerodynamic coefficients requires detailed knowledge of the aircraft’s design. These designs and parameters are well protected by aircraft manufacturers. They rarely can be used in public research. Very detailed aerodynamic...

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...

Aircraft initial mass estimation using Bayesian inference method

Aircraft mass is a crucial piece of information for studies on aircraft performance, trajectory prediction, and many other topics of aircraft traffic management. However, It is a common challenge for researchers, as well as air traffic control, to access this proprietary information. Previously, several studies have proposed methods to estimate...

Estimating aircraft drag polar using open flight surveillance data and a stochastic total energy model

In air traffic management research, aircraft performance models are often used to generate and analyze aircraft trajectories. Although a crucial part of the aircraft performance model, the aerodynamic property of aircraft is rarely available for public research purposes, as it is protected by aircraft manufacturers for commercial reasons. In...

WRAP: An open-source kinematic aircraft performance model

Open access to flight data from Automatic Dependent Surveillance-Broadcast (ADS-B) has provided researchers with 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...

OpenAP: An open-source aircraft performance model for air transportation studies and simulations

Air traffic simulations serve as common practice to evaluate different concepts and methods for air transportation studies. The aircraft performance model is a key element that supports these simulation-based studies. It is also an important component for simulation-independent studies, such as air traffic optimization and prediction studies....

pyModeS: Decoding Mode-S Surveillance Data for Open Air Transportation Research

The availability of low-cost automatic dependent surveillance-broadcast (ADS-B) receivers has given researchers the ability to make use of large amounts of aircraft state data. This data is being used to support air transportation research in performance study, trajectory prediction, procedure analysis, and airspace design. However, aircraft...

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...

Particle filter for aircraft mass estimation and uncertainty modeling

This article investigates the estimation of aircraft mass and thrust settings of departing aircraft using a recursive Bayesian method called particle filtering. The method is based on a nonlinear state-space system derived from aircraft point-mass performance models. Using only aircraft surveillance data, flight states such as position,...

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....