NDLI: Fixed point implementation of fast Kalman predictors

Content Provider	IEEE Xplore Digital Library
Author	Scharf, L. Sigurdsson, S.
Copyright Year	1963
Abstract	In this note we study scaling rules and roundoff noise variances in a fixed-point implementation of the Kalman predictor for an ARMA time series observed noise free. The Kalman predictor is realized in a fast form that uses the so-called fast Kalman gain algorithm. The algorithm for the gain is fixed point. Scaling rules and expressions for rounding error variances are derived. The numerical results show that the fixed-point realization performs very close to the floating point realization for relatively low-order ARMA time series that are not too narrow band. The predictor has been implemented in 16-bit fixed-point arithmetic on an INTEL 8086 microprocessor, and in 16-bit floating-point arithmetic on an INTEL 8080. Fixed-point code was written in Assembly language and floating-point code was written in Fortran. Experimental results were obtained by running the fixed- and floating-point filters on identical data sets. All experiments were carried out on an INTEL MIDS 230 development system.
Sponsorship	IEEE Control Systems Society
Starting Page	850
Ending Page	852
Page Count	3
File Size	282330
File Format	PDF
ISSN	00189286
Volume Number	29
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1984-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kalman filters Technological innovation Equations Fixed-point arithmetic Statistics Filtering Narrowband Microprocessors Floating-point arithmetic Assembly
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering Computer Science Applications

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