Journal article
Classification of radar clutter using neural networks
Abstract
A classifier that incorporates both preprocessing and postprocessing procedures as well as a multilayer feedforward network (based on the back-propagation algorithm) in its design to distinguish between several major classes of radar returns including weather, birds, and aircraft is described. The classifier achieves an average classification accuracy of 89% on generalization for data collected during a single scan of the radar antenna. The …
Authors
Haykin S; Deng C
Journal
IEEE Transactions on Neural Networks and Learning Systems, Vol. 2, No. 6, pp. 589–600
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication Date
1991
DOI
10.1109/72.97936
ISSN
2162-237X