DocumentCode :
294994
Title :
The Kantorovich inequality for error analysis of the Kalman filter with unknown noise distributions
Author :
Spall, James C.
Author_Institution :
Appl. Phys. Lab., Johns Hopkins Univ., Laurel, MD, USA
Volume :
2
fYear :
1995
fDate :
13-15 Dec 1995
Firstpage :
1553
Abstract :
The state-space model with random noises is widely used to model dynamic systems. In many practical problems, the noise terms will have unknown probability distributions, which is contrary to the usual assumption of Gaussian noises made in state-vector estimation; this assumption is usually made for reasons of mathematical tractability. A problem arises, however, in that inference based on the incorrect Gaussian assumption can lead to misleading or erroneous conclusions. This note shows how the Kantorovich inequality from probability theory has potential for characterizing the estimation error of a Kalman filter in such a non-Gaussian (distribution-free) setting
Keywords :
Gaussian noise; Kalman filters; error analysis; probability; random noise; state estimation; state-space methods; Gaussian noises; Kalman filter; Kantorovich inequality; dynamic systems; error analysis; probability distributions; probability theory; state-space model; state-vector estimation; unknown noise distributions; Covariance matrix; Electronic mail; Error analysis; Filters; Gaussian noise; Laboratories; Physics; Probability distribution; State estimation; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 1995., Proceedings of the 34th IEEE Conference on
Conference_Location :
New Orleans, LA
ISSN :
0191-2216
Print_ISBN :
0-7803-2685-7
Type :
conf
DOI :
10.1109/CDC.1995.480358
Filename :
480358
Link To Document :
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