Neural networks for data fusion
Sanjay Chaudhuri, Shaimanti Das · 2002
The application of artificial neural network technology to data fusion for target recognition is discussed. The specific application includes airborne target recognition primarily using information available from radar and EO-IR thermal imaging sensors. The artificial neural network based fusion architectures from alternative approaches are discussed, such as alternative learning algorithms, a training set, and massively parallel distributed processing for making real-time automatic target recognition decisions. The experimental results indicate that target recognition performance can be greatly enhanced by using an array of complementary sensors whose outputs are fused to extract information not otherwise available from a single sensor