Abstract
An approach to federated filtering in hybrid coordinates is presented for a maneuvering target tracking through a multi-passive-sensor system. This new design accommodates a group of extended Kalman filters that the sensor-dedicated local processors process angle-only measurements extracted from a number of associated maneuverable aircrafts with onboard direction finders. Each filter utilizes the Reference Cartesian Coordinate (RCC) system for state and state covariance extrapolation and utilizes the modified spherical coordinate system for state and state covariance updating. In addition, a discrete-time state equation with the piecewise constant white target acceleration model is introduced into the RCC system for federated filtering. A weighted least squares estimator is used for the global processor aggregating the local estimates to generate a global estimate in the local inertial Cartesian coordinate system. Simulation results show that proposed approach drastically improves the tracking accuracy.
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