Title :
Exact finite-dimensional nonlinear filters
Author :
Daum, Frederick E.
Author_Institution :
Raytheon Company, Wayland, MA, USA
fDate :
7/1/1986 12:00:00 AM
Abstract :
A new nonlinear filter is derived for continuous-time processes with discrete-time measurements. The filter is exact, and it can be implemented in real time with a computational complexity that is comparable to the Kalman filter. This new filter includes both the Kalman filter and the discrete-time version of the Benes filter as special cases. Moreover, the new theory can handle a large class of nonlinear estimation problems that cannot be solved using the Kalman or discrete-time Benes filters. A simple approximation technique is suggested for practical applications in which the dynamics do not satisfy the required conditions exactly. This approximation is analogous to the so-called "extended Kalman filter" [10], and it represents a generalization of the standard linearization method.
Keywords :
Kalman filtering, nonlinear systems; Nonlinear filtering; State estimation, nonlinear systems; Computational complexity; Difference equations; Differential equations; Filtering theory; Gaussian noise; Kalman filters; Nonlinear equations; Nonlinear filters; Random processes; Random variables;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1986.1104344