Augmented state multiple model probability data association track fusion for air traffic control

Abstract

ADS-B and radar will coexist for a long time in the future. For the ADS-B and multi-radar asynchronous track fusion problem in the air traffic control system, an ADS-B and radar fusion architecture and an asynchronous multi-sensor track fusion algorithm based on augmented state interacting multiple model(IMM) filter with probability data association(PDA) are proposed in this paper. The fusion algorithm is developed by applying the standard IMM approach, the PDA technique, and asynchronous measurement updating to a state-augmented system for the target motion. The state vector is augmented to include the past states which correspond to those asynchronous measurements. A PDA filter for parallel sensor processing is developed for target tracking under clutter. Real data from the ADS-B equipped aircraft and radar are used to test the performance of the algorithm. The simulation result shows that the track accuracy can be improved by this algorithm and the performance is comparable with the distributed multi-rate track fusion algorithm.