A contribution to performance prediction for probabilistic data association tracking filters
Kershaw DJ., Evans RJ.
The probabilistic data association (PDA) algorithm for tracking in clutter contains a stochastic (data-dependent) Riccati equation for updating the estimation error covariance matrix. This note details a simple analytic approximation to the stochastic Riccati equation that allows precomputation of the estimation error covariance matrices. The potential of the approximation for performance analysis of PDA-based tracking algorithms is demonstrated using a simple example. © 1996 IEEE.