Modelling ADS-B Reception Probability Using OpenSky Data

Abstract

This paper introduces a model for estimating ADS-B (Automatic Dependent Surveillance-Broadcast) reception probability based on OpenSky network data. The methodology derives reception probability from the distribution of ADS-B message update intervals by examining variations in interval "bumps" around the 0.5-second transmission frequency, shaped by system jitter. Only sensors with circular coverage are used to ensure uniform reception probability estimation. Key variables such as distance, air traffic, and airport interference are binned and used in regression analysis to estimate model constants. Results demonstrate that this model achieves a lower Root Mean Square Error (RMSE) compared to Chung's model, indicating higher accuracy. However, challenges remain in capturing complex interactions between distance, traffic, and airports in proximity, partly due to unmodeled interdependencies and these features serve as proxies to the dependent variable. Further investigation of these relationships could enhance the model's depiction of ADS-B reception probability.