ISSN:
1573-2878
Keywords:
Imaging systems
;
filtering
;
prediction
;
estimation
;
stochastic differential equations
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract The equations of state evolution of a hybrid system are nonlinear and generate non-Gaussian sample paths. For this reason, the optimal, mean-square estimate of the state is difficult to determine. In an earlier paper (Ref. 1), a useful approximation to the optimal estimator was derived for the case where there is a direct, albeit noisy, measurement of the modal state. Although this algorithm has proven serviceable, it is restricted to applications in which the base-state path is continuous. In this paper, the result is extended to the case in which there are base-state discontinuities of a particular sort. The algorithm is tested on a target tracking problem and is shown to be superior to both the extended Kalman filter and the estimator derived in Ref. 1.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1022618500543
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