Fuzzy control in the deployable autonomous distributed system

Peter J. Shea; Mark W. Owen; George Chadderdon

doi:10.1117/12.357163

27 July 1999 Fuzzy control in the deployable autonomous distributed system

Peter J. Shea, Mark W. Owen, George Chadderdon

Proceedings Volume 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII; (1999) https://doi.org/10.1117/12.357163
Event: AeroSense '99, 1999, Orlando, FL, United States

Abstract

The Deployable Autonomous Distributed System is an ocean surveillance system that contains a field of sensor nodes. Each sensor node provides target detections to a master node in the field for fusion by a Multiple Hypothesis Tracker Correlator (MHTC). The overall performance of a fusion engine depends upon the set of parameters that are used by the Multiple Hypothesis Tracker. Although a static set of parameters may work well over a wide range of scenarios, they may not lead to optimal performance in all cases. This paper addresses Level 4 fusion to improve performance of the data fusion system at the master node by using a fuzzy logic controller to adaptively tune the parameters. By using a set of linguistic rule based fuzzy logic algorithms, the tuning parameters of the MHTC are modified. A set of metrics are used to determine the added worth of the fuzzy logic controller.

Citation Download Citation

Peter J. Shea, Mark W. Owen, and George Chadderdon "Fuzzy control in the deployable autonomous distributed system", Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); https://doi.org/10.1117/12.357163

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