Title :
A differential geometric approach to nonlinear filtering: the projection filter
Author :
Brigo, Damiano ; Hanzon, Bernard ; LeGland, Francois
Author_Institution :
CARIPLO Bank, Milan, Italy
fDate :
2/1/1998 12:00:00 AM
Abstract :
This paper presents a new and systematic method of approximating exact nonlinear filters with finite dimensional filters, using the differential geometric approach to statistics. The projection filter is defined rigorously in the case of exponential families. A convenient exponential family is proposed which allows one to simplify the projection filter equation and to define an a posteriori measure of the local error of the projection filter approximation. Finally, simulation results are discussed for the cubic sensor problem
Keywords :
differential geometry; filtering theory; nonlinear filters; probability; statistical analysis; cubic sensor; differential geometry; exponential families; finite dimensional filters; nonlinear filtering; nonlinear filters; probability; projection filter; Density measurement; Differential equations; Filtering; Geometry; Nonlinear equations; Nonlinear filters; Partial differential equations; State estimation; Statistics; Stochastic processes;
Journal_Title :
Automatic Control, IEEE Transactions on
