Leveraging local ADS-B transmissions to assess the performance of air traffic at general aviation airports

This paper presents details of a novel hardware and software architecture for locally and automatically recording air traffic operations data at general aviation airports, including those that primarily serve smaller aircraft and may not have any other means, such as control towers, to collect such data. The platform is based on ADS-B data collected at 1090 and 978 MHz. We describe its deployment on the Amazon Web Services cloud computing environment. Various pre-processing and filtering stages are demonstrated to clean up the data. Some techniques for dealing with unreliable data are described. Finally, we show how to use the resulting data to compile air traffic performance metrics of interest for small airports, including aircraft approach speeds and runway occupancy times. These metrics may then be used to support enhanced models of airport capacity for these facilities.