Multisensor data fusion for obstacle tracking using neuro-fuzzy estimation algorithms

Rory S. Doyle; Chris J. Harris

doi:10.1117/12.179031

22 June 1994 Multisensor data fusion for obstacle tracking using neuro-fuzzy estimation algorithms

Rory S. Doyle, Chris J. Harris

Proceedings Volume 2233, Sensor Fusion and Aerospace Applications II; (1994) https://doi.org/10.1117/12.179031
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

The problem addressed in this paper is that of estimating the tracks of dynamic obstacles in the environment of a helicopter operating in hazardous conditions. Fuzzy logic and neural networks have shown their strength in recent years in the solutions to non-linear problems. The aim of this paper is to present neuro-fuzzy data fusion algorithms which can be used to fuse information provided by multiple spatially separate sensors engaged in the tracking of obstacles whose dynamics are a priori unknown.

Citation Download Citation

Rory S. Doyle and Chris J. Harris "Multisensor data fusion for obstacle tracking using neuro-fuzzy estimation algorithms", Proc. SPIE 2233, Sensor Fusion and Aerospace Applications II, (22 June 1994); https://doi.org/10.1117/12.179031

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