Title :
Stochastic estimation using a continuum of models
Author :
Layne, Jeffery ; Weaver, Scott
Author_Institution :
Wright Res. & Dev. Center, Wright-Patterson AFB, OH, USA
Abstract :
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.
Keywords :
Kalman filters; parameter estimation; probability; sensor fusion; symmetry; target tracking; Generalized Pseudo-Bayesian; Kalman filtering; continuum of models; multiple model estimation; recursive multiple model tracking; stochastic estimation; symmetry problem; target tracking; Acceleration; Adaptation model; Aerospace electronics; Filtering; Kalman filters; Predictive models; Stochastic processes; Target tracking; Uncertainty; Weight measurement;
Conference_Titel :
Information Fusion, 2000. FUSION 2000. Proceedings of the Third International Conference on
Conference_Location :
Paris, France
Print_ISBN :
2-7257-0000-0
DOI :
10.1109/IFIC.2000.862660
