Date of Award


Degree Type


Degree Name

Doctor of Philosophy (PhD)



Committee Chair

Mary E. Johnson

Committee Member 1

Thomas Q. Carney

Committee Member 2

Richard O. Fanjoy

Committee Member 3

John A. Springer


The International Civil Aviation Organization (ICAO) and major airlines believe that flight data analysis is an effective approach to mitigate the risk of aviation accidents (International Civil Aviation Organization, 2010; International Air Transport Association, 2016). In the United States, flight data analysis is encouraged by the Federal Aviation Administration (FAA) through the flight operational quality assurance (FOQA) program. Among all aviation activities, general aviation (GA) has the highest accident rate (National Transportation Safety Board, 2014). However, implementation of flight data analysis for GA not only requires expensive investment on flight data recording devices, but also increases long-term labor cost due to regular data collection and data analysis. Automatic Dependent Surveillance Broadcast Out (ADS-B Out) is a precise satellite-based surveillance system that periodically broadcasts flight data retrieved from satellites and onboard avionics of the ADS-B Out capable aircraft. Based on the standard technical provisions of the ADS-B Out, the use of ADS-B data is expected to be a possible approach to facilitate the flight data analysis for general aviation. This research explored the use of ADS-B data to facilitate flight data analysis for general aviation.

Researchers started the current study phase from analyzing the structure and content of the ADSB message by referring to the ICAO technical provisions (2008) and the operational performance standard of ADS-B from the Radio Technical Commission for Aeronautics (RTCA) (2009). Based upon the findings of the ADS-B data structure and content, a set of retrievable aircraft parameters was identified, and additional aircraft parameters were derived from the basic ADS-B information. Furthermore, sets of flight metrics were developed using the aircraft parameters broadcasted by ADS-B Out. The development of flight metrics was expected to be essential for measuring flight operational performance to support flight data analysis. In addition, exceedance detection was adopted to analyze the flight metrics in flight data analysis. ADS-B data were collected using an ADS-B receiver, and 40 sets of ADS-B data were selected to detect five operational exceedances of the Cirrus SR-20 aircraft of the Purdue Fleet. Exceedances were detected from the 40 sets of data. However, researchers noticed that the sparse ADS-B data caused by the low reception rate might affect the exceedance detection. Therefore, a preliminary analysis was conducted to investigate the difference of exceedance detection using ADS-B data with different reception rates. The results of analysis indicated that sparse ADS-B data could affect the detection of exceedances, but some exceedances might be less sensitive to the sparse data. Based on the findings of this research, recommendations were proposed for future studies.