Title :
Generalized Kalman filter for discrete-continuous Markov processes
Author_Institution :
Inst. of Control Sci., Acad. of Sci., Moscow, Russia
Abstract :
This paper deals with the filtering problem for the partially observable vector-processes in the case when unobservable process is excited by a Markov process with a finite state space, and the process of observations is a semimartingale with non-Gaussian martingale part. All the processes are described by Ito´s stochastic differential equations with measure.
Keywords :
Gaussian processes; Kalman filters; Markov processes; differential equations; filtering theory; observability; state-space methods; Ito stochastic differential equations; Kalman filter; discrete-continuous Markov processes; filtering problem; finite state space; nonGaussian martingale part; partially observable vector processes; semimartingale; unobservable process; Equations; Extraterrestrial measurements; Filtering; Gaussian processes; Indium tin oxide; Markov processes; Nonlinear filters; Q measurement; State-space methods; Stochastic processes;
Conference_Titel :
Decision and Control, 2002, Proceedings of the 41st IEEE Conference on
Print_ISBN :
0-7803-7516-5
DOI :
10.1109/CDC.2002.1184958
