Characterisation of adaptive filters for air traffic control

Abstract

This paper discusses the possibilities of employing adaptive filtering techniques for tracking of a civilian aircraft in Air traffic control scenario. Position and velocity of the aircraft have been estimated by Adaptive Kalman filters and Adaptive Extended Kalman filters using Standard Uniform motion (UM) and Coordinated turn (CT) models. The performances of the adaptive estimators for such cases have been evaluated using Monte Carlo simulations while process noise statistics are unknown. It has been studied that the adaptive schemes deliver substantially improved tracking performances over non-adaptive schemes, for model errors and process noise uncertainties. From the RMSE results, it has also been found that the non-linear Coordinated Turn model exhibits better performance than linear Uniform Motion model for all estimation techniques. Scaling factor based g-Adaptive technique has been employed for adaptation purposes. The effect of different window sizes on the performance of the adaptive filters has also been studied.