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Proceedings Paper

Sensor management in an ASW data fusion system
Author(s): Dawn E. Penny
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Paper Abstract

The Multi-Sensor Fusion Management (MSFM) algorithm positions multiple, detection-only, passive sensors in a 2D plane to optimize the fused probability of detection using a simple decision fusion method. Previously the MSFM algorithm was evaluated on two synthetic problem domains comprising of both static and moving targets. In the original formulation the probability distribution of the target location was modelled using a non-parametric approach. The logarithm of the fused detection probability was used as a criterion function for the optimisation of the sensor positions. This optimisation used a straightforward gradient ascent approach, which occasionally found local optima. Following the placement optimisation the sensors were deployed and the individual sensor detections combined using a logical OR fusion rule. The target location distribution could then be updated using the method of sampling, importance re-sampling (SIR). In the current work the algorithm is extended to admit a richer variety of behaviour. More realistic sensor characteristic models are used which include detection-plus-bearing sensors and false alarm probabilities commensurate with actual sonar sensor systems. In this paper the performance of the updated MSFM algorithm is illustrated on a realistic anti-submarine warfare (ASW) application in which the placement of the sensors is carried out incrementally, allowing for the optimisation of both the location and the number of sensors to be deployed.

Paper Details

Date Published: 12 March 1999
PDF: 12 pages
Proc. SPIE 3719, Sensor Fusion: Architectures, Algorithms, and Applications III, (12 March 1999); doi: 10.1117/12.341365
Show Author Affiliations
Dawn E. Penny, Defence Evaluation and Research Agency Malvern (United Kingdom)

Published in SPIE Proceedings Vol. 3719:
Sensor Fusion: Architectures, Algorithms, and Applications III
Belur V. Dasarathy, Editor(s)

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