Stochastic estimation using a continuum of models
J. Layne, S. Weaver · 2000
We investigate a recursive multiple model tracking approach similar to the Generalized Pseudo-Bayesian 1 (GPB1) (Bar-Shalom and Li, 1993) approach. However, we consider a continuum of models rather than the discrete set that is usually implemented in the GPBI method. By doing so better models are available to improve tracker performance and solve the symmetry problem inherent in most multiple model approaches.