DocumentCode
882444
Title
A modified Gaussian sum approach to estimation of non-Gaussian signals
Author
Caputi, Mauro J. ; Moose, Richard L.
Author_Institution
Dept. of Eng., Hofstra Univ., Hempstead, NY, USA
Volume
29
Issue
2
fYear
1993
fDate
4/1/1993 12:00:00 AM
Firstpage
446
Lastpage
451
Abstract
A Gaussian sum estimation algorithm has previously been developed to deal with noise processes that are non-Gaussian. Inherent in this algorithm is a serious growing memory problem that causes the number of terms in the Gaussian sum to increase exponentially at each iteration. A modified Gaussian sum estimation algorithm using an adaptive filter is developed that avoids the growing memory problem of the previous algorithm while providing effective state estimation. The adaptive filter is comprised of a fixed set of estimators operating in parallel with each individual estimate possessing its own corresponding weighting term. A simulation example illustrates the new non-Gaussian estimation technique
Keywords
Kalman filters; adaptive filters; digital filters; digital simulation; noise; parallel processing; signal processing; state estimation; Kalman filter; adaptive filter; estimation algorithm; memory; modified Gaussian sum; noise; nonGaussian noise; simulation; state estimation; Adaptive filters; Approximation algorithms; Density functional theory; Density measurement; Gaussian noise; Markov processes; Probability; Random processes; Random variables; Signal processing; State estimation;
fLanguage
English
Journal_Title
Aerospace and Electronic Systems, IEEE Transactions on
Publisher
ieee
ISSN
0018-9251
Type
jour
DOI
10.1109/7.210082
Filename
210082
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