A Continuum of Models for Stochastic Estimation
Jeffery R. Layne, Scott Weaver · 2000
In this paper, we investigate a recursive multiple model tracking approach similar to the Generalized Pseudo-Bayesian I (GPBI) I approach. However, here 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 bias problem inherent in most multiple model approaches.