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Proceedings Paper

Optimal polarizations for radar detection and recognition of targets in clutter
Author(s): Leslie M. Novak; Steven R. Hesse
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Paper Abstract

In previous studies, simple polarimetric target and clutter models were used to derive algorithms for optimal processing of fully polarimetric measurement data. The optimal polarimetric matched filter (PMF) was derived and its performance evaluated. It was suggested that the target model used in these studies was too simple and that a more realistic target model should be developed--one which characterizes a target's polarimetric returns as a function aspect angle around the target. This is a reasonable research topic to investigate since the polarimetric properties of a target may vary significantly with viewing angle (e.g., a target imaged at broadside looks much different than a target imaged 45 degree(s) off broadside). In our previous work, targets were characterized by their polarization covariance matrices, which were calculated by averaging fully polarimetric turntable measurements of targets over 360 degree(s) of aspect. This paper investigates the variation in the target polarization covariance matrix versus aspect angle, and quantified its effect on the target-to-clutter ratio.

Paper Details

Date Published: 16 September 1992
PDF: 5 pages
Proc. SPIE 1700, Automatic Object Recognition II, (16 September 1992); doi: 10.1117/12.138261
Show Author Affiliations
Leslie M. Novak, Lincoln Lab./MIT (United States)
Steven R. Hesse, Lincoln Lab./MIT (United States)

Published in SPIE Proceedings Vol. 1700:
Automatic Object Recognition II
Firooz A. Sadjadi, Editor(s)

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