Hybrid fuzzy-neural classifier for feature level data fusion in ladar autonomous target recognition

Stephen Soliday; Melissa Tay Perona; Daniel G. McCauley

doi:10.1117/12.445409

22 October 2001 Hybrid fuzzy-neural classifier for feature level data fusion in ladar autonomous target recognition

Stephen Soliday, Melissa Tay Perona, Daniel G. McCauley

Proceedings Volume 4379, Automatic Target Recognition XI; (2001) https://doi.org/10.1117/12.445409
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

This paper will discuss the design of a hybrid fuzzy-neural classifier for fusion of range and intensity channels coming from a LADAR sensor. Fusion was performed on a feature rather than pixel level. Results will be compared between ATR performance with and with out fusion. Also, discussed in this paper is the use of genetic algorithms for the training and optimization of the ATR system with a limited set of ground truth.

Citation Download Citation

Stephen Soliday, Melissa Tay Perona, and Daniel G. McCauley "Hybrid fuzzy-neural classifier for feature level data fusion in ladar autonomous target recognition", Proc. SPIE 4379, Automatic Target Recognition XI, (22 October 2001); https://doi.org/10.1117/12.445409

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