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Proceedings Paper

Nonlinear adaptive filter for closed-loop fire control
Author(s): William C. Marshall
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Paper Abstract

This paper presents an adaptive or self-learning filter design intended for use in real-time closed loop pointing control systems engaging multiple targets. The design approach is based upon use of a performance index (based upon the Mahalanobis generalized distance function) and multiple filters processed in parallel using the same nonlinear measurements as input. Application of performance index criteria to the statistics of individual filter residuals allows the selection of the optimum filter set without the time delays typically encountered and thereby allows the composite filter structure to adapt (or self-learn) to uncertainties in modeling target acceleration capabilities. An advantage of this approach is that it also provides to an operator (or a robotic controller) the confidence level of tracking system performance against a maneuvering target. This information is of interest for deployment of counter-measures (e.g., fire control eventing, alarms, engagement priority, etc) or simply for laboratory system tests of design adequacy.

Paper Details

Date Published: 1 September 1990
PDF: 12 pages
Proc. SPIE 1310, Signal and Image Processing Systems Performance Evaluation, (1 September 1990); doi: 10.1117/12.21793
Show Author Affiliations
William C. Marshall, Honeywell Systems and Research (United States)

Published in SPIE Proceedings Vol. 1310:
Signal and Image Processing Systems Performance Evaluation
Hatem N. Nasr; Firooz A. Sadjadi, Editor(s)

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