Distributed data fusion algorithms for tracking a maneuvering target

Abstract

The focus of this paper is on examining the accuracy of two existing state vector fusion methods, weighted covariance fusion (WCF) and information matrix fusion (IMF), in a multi-sensor environment for computing the fused estimates from distributed Kahnan filters tracking a single maneuvering target. Each sensor tracker utilized in the Reference Cartesian Coordinate System (RCCS) is described for target tracking when the radar measures range, bearing and elevation angle in the Spherical Coordinate System (SCS). Simulation results show that the IMF method has more efficient and robust capabilities of improving tracking accuracy than the WCF method.