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Proceedings Paper

Adaptive resource allocation architecture applied to line tracking
Author(s): Mark W. Owen; Donald W. Pace
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Paper Abstract

Recent research has demonstrated the benefits of a multiple hypothesis, multiple model sonar line tracking solution, achieved at significant computational cost. We have developed an adaptive architecture that trades computational resources for algorithm complexity based on environmental conditions. A Fuzzy Logic Rule-Based approach is applied to adaptively assign algorithmic resources to meet system requirements. The resources allocated by the Fuzzy Logic algorithm include (1) the number of hypotheses permitted (yielding multi-hypothesis and single-hypothesis modes), (2) the number of signal models to use (yielding an interacting multiple model capability), (3) a new track likelihood for hypothesis generation, (4) track attribute evaluator activation (for signal to noise ratio, frequency bandwidth, and others), and (5) adaptive cluster threshold control. Algorithm allocation is driven by a comparison of current throughput rates to a desired real time rate. The Fuzzy Logic Controlled (FLC) line tracker, a single hypothesis line tracker, and a multiple hypothesis line tracker are compared on real sonar data. System resource usage results demonstrate the utility of the FLC line tracker.

Paper Details

Date Published: 3 April 2000
PDF: 10 pages
Proc. SPIE 4051, Sensor Fusion: Architectures, Algorithms, and Applications IV, (3 April 2000); doi: 10.1117/12.381652
Show Author Affiliations
Mark W. Owen, SPAWAR Systems Ctr. (United States)
Donald W. Pace, ORINCON Corp. (United States)

Published in SPIE Proceedings Vol. 4051:
Sensor Fusion: Architectures, Algorithms, and Applications IV
Belur V. Dasarathy, Editor(s)

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