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Bounding filter - A simple solution to lack of exact a priori statistics.Wiener and Kalman-Bucy estimation problems assume that models describing the signal and noise stochastic processes are exactly known. When this modeling information, i.e., the signal and noise spectral densities for Wiener filter and the signal and noise dynamic system and disturbing noise representations for Kalman-Bucy filtering, is inexactly known, then the filter's performance is suboptimal and may even exhibit apparent divergence. In this paper a system is designed whereby the actual estimation error covariance is bounded by the covariance calculated by the estimator. Therefore, the estimator obtains a bound on the actual error covariance which is not available, and also prevents its apparent divergence.
Document ID
19730035801
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Nahi, N. E.
(Southern California, University Los Angeles, Calif., United States)
Weiss, I. M.
(North American Rockwell Corp. Autonetics Div., Anaheim, Calif., United States)
Date Acquired
August 7, 2013
Publication Date
January 1, 1972
Subject Category
Electronics
Meeting Information
Meeting: Conference on Decision and Control and Symposium on Adaptive Processes
Location: New Orleans, LA
Start Date: December 13, 1972
End Date: December 15, 1972
Accession Number
73A20603
Funding Number(s)
CONTRACT_GRANT: NGL-05-018-044
Distribution Limits
Public
Copyright
Other

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