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Classification of radar clutter using neural...
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