Asynchronous Multi-sensor Data Fusion with Decentralized IMM-PDAF
W. J. Park, Chang Ho Kang, Sang Yeob Kim, Chunghoon Park · 2018
In this paper, asynchronous multi-sensor fusion with decentralized IMM-PDAF is designed. To improve the estimation performance for the maneuvering target in clutter, interacting multiple model (IMM) based probabilistic data association filter (PDAF) is utilized, and multiple sensors are assumed to be asynchronous to reflect the real multi-sensor application. To verify the tracking filter, simulations for tracking maneuvering target with asynchronous multi-sensor fusion are carried out. The simulation results show that the designed filter tracks target robustly, and fusing asynchronous multi-sensor reduces the estimation error.