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Proceedings Paper

Systolic Architecture For Extended Kalman Filtering
Author(s): Timothy C. Phillips; Ralph Fabrizio
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Paper Abstract

Extended Kalman filtering provides for non-linearities in the equations of motion by propagating the state per a differential equation. For the predictor part of the Kalman filter, the Runge-Kutta differential equation solver can be used to extrapolate each new state numerically. This paper explores the systolic implementation of the Runge-Kutta algorithm. For the corrector part of the Kalman filter, this paper outlines an ESL realization of a systolic array backsolver.

Paper Details

Date Published: 21 January 1988
PDF: 8 pages
Proc. SPIE 0826, Advanced Algorithms and Architectures for Signal Processing II, (21 January 1988); doi: 10.1117/12.942012
Show Author Affiliations
Timothy C. Phillips, ESL Inc. (United States)
Ralph Fabrizio, ESL Inc. (United States)


Published in SPIE Proceedings Vol. 0826:
Advanced Algorithms and Architectures for Signal Processing II
Franklin T. Luk, Editor(s)

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