Multiple-target tracking using an extended Kalman filter
Edward W. Kamen, Chellury Ram Sastry · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
ABSTRACT The paper centers on the continued development of the symmetric measurement equation (SME)filter developed by Kamen' for track maintenance in multiple target tracking. In this approach there is noneed to correctly associate measurements and targets before target state estimation can take place. Rather the data association problem is embedded in the process of target state estimation. The first order version of the SME filter is an extended Kalman filter (EKF), and thus the computational requirementsfor filter implementation are comparable to that for a standard Kalman filter. In addition, in contrast toprobabilistic data association filters, the estimator does not rely on the computation of probabilities forcorrect measurement/target associations. The SME filter is based on a standard state model for the targetstate trajectories. However, in contrast to existing approaches, the measurements are defmed in terms of nonlinear symmetric functionals of the target positions, except for one of the measurements which is