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Proceedings Paper

Clutter cancellation and sea-ice detection using artificial neural network
Author(s): Henry Leung; Martin Blanchette; Simon Haykin
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Paper Abstract

Neural processing of microwave sea echo is proposed for the suppression of strong reflections from scatterers on the ocean surface, commonly referred as sea clutter. A radial basis function (RBF) neural network is shown to be effective for this purpose based on real experimental data. In addition, using the RBF neural network as a model for sea clutter, a novel adaptive detection technique is introduced and applied to the problem of detection of growlers (small fragments of icebergs) in sea clutter. The performance of this new detection method is shown to be superior to that of a conventional detector for the real data sets used in this paper.

Paper Details

Date Published: 2 September 1993
PDF: 12 pages
Proc. SPIE 1965, Applications of Artificial Neural Networks IV, (2 September 1993); doi: 10.1117/12.152531
Show Author Affiliations
Henry Leung, Defence Research Establishment Ottawa (Canada)
Martin Blanchette, Defence Research Establishment Ottawa (Canada)
Simon Haykin, McMaster Univ. (Canada)


Published in SPIE Proceedings Vol. 1965:
Applications of Artificial Neural Networks IV
Steven K. Rogers, Editor(s)

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