The symmetric measurement equation (SME) approach to multiple target
tracking is revisited using unscented Kalman and particle filters. The unscented Kalman
filter (UKF) promises more accurate approximation of
nonlinearities and simpler implementation of the SME approach than
the EKF. The particle filter implementation offers the ability to
explore the limits of the SME approach. In the first portion of this paper, experiences with SME for tracking one-dimensional motion are reviewed. The second portion of this paper discusses the challenges that arise when using the SME approach to track two-dimensional motion and introduces a new set of two-dimensional SME equations. Finally, Taylor series expansions are used to explore differences between Kalman filter-SME pairings. Using the Taylor series representation, we show how the choice of SME formulation affects the representation, and consequently
approximation, of uncertainty in the Kalman filters.