Title :
On the Mortensen equation for maximum likelihood state estimation
Author :
Aihara, Shin Ichi ; Bagchi, Arunabha
Author_Institution :
Dept. of Manage. & Syst. Sci., Sci. Univ. of Tokyo, Japan
fDate :
10/1/1999 12:00:00 AM
Abstract :
The main purpose of the paper is to formulate the maximum likelihood state estimation problem correctly for a continuous-time nonlinear stochastic dynamical system. By using the Onsager-Machlup functional, a modified likelihood is introduced. The basic equation for the maximum likelihood state estimate is derived with the aid of a dynamic programming approach. The numerical procedure for realizing the recursive filtering is also proposed with some numerical results
Keywords :
continuous time systems; dynamic programming; filtering theory; functional equations; maximum likelihood estimation; nonlinear systems; recursive estimation; state estimation; stochastic systems; Mortensen equation; Onsager-Machlup functional; continuous-time nonlinear stochastic dynamical system; maximum likelihood state estimation; recursive filtering; Additive white noise; Dynamic programming; Filtering; Filters; Maximum likelihood estimation; Nonlinear equations; Probability; State estimation; Stochastic processes; Stochastic systems;
Journal_Title :
Automatic Control, IEEE Transactions on
