Track-independent estimation schemes for registration in a network of sensors
H. Abbas, Donglai Xue, M. Farooq, G. Parkinson, Martin Blanchette · 2002
Several methods for estimating registration biases in a network of sensors are presented in this paper. These methods are track-independent meaning that they do not require assumptions on target dynamics models. Based on the simulation studies, the applicability, accuracy and efficiency of these methods are discussed and compared with the track-dependent Kalman filtering method. Recommendations are made on the choice of the methods.