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Proceedings Paper

Performance of a multiresolution classifier using enhanced-resolution SAR data
Author(s): Gregory J. Owirka; Alison L. Weaver; Leslie M. Novak
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Paper Abstract

MIT Lincoln Laboratory has developed a complete, end-to-end, automatic target detection/recognition system for synthetic aperture radar data. The system uses resolution enhancement (super-resolution) techniques to improve the performance of the automatic target recognition stage. This paper presents a new multi-resolution classification scheme that greatly improves the computational efficiency of the classifier with only a slight loss in classification performance.

Paper Details

Date Published: 10 June 1997
PDF: 11 pages
Proc. SPIE 3066, Radar Sensor Technology II, (10 June 1997); doi: 10.1117/12.276091
Show Author Affiliations
Gregory J. Owirka, MIT Lincoln Lab. (United States)
Alison L. Weaver, MIT Lincoln Lab. (United States)
Leslie M. Novak, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 3066:
Radar Sensor Technology II
Robert Trebits; James L. Kurtz, Editor(s)

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