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Proceedings Paper

Benefits of aspect diversity for SAR ATR: fundamental and experimental results
Author(s): Gary F. Brendel; Larry L. Horowitz
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Paper Abstract

This paper continues the study reported in Ref. 1 and Ref. 2 trading off the fundamental ATR performance capability (i.e., algorithm-independent) of various SAR design options. The previous papers considered the performance impact of SAR range/cross-range resolution and compared the use of 1-D HRR (high-range-resolution radar) versus 2-D SAR, versus multisensor, 3-D SAR. The work reported here extends the SAR and HRR results of Ref. 2 to include aspect diversity in the SAR measurements. We show that SAR and HRR are benefited by multi-aspect measurements mostly because multiple views add diversity: poorer views benefit from having better views combined in a multi-aspect classifier. Finally, as a proof of concept, multi-aspect diversity is incorporated into an existing SAR ATR classifier; performance of an MSTAR 10-class MSE classifier is shown to improve substantially. A major tenet is verified by the experimental results: added measurement domains, such as aspect diversity, which separate the target signature vectors in the observation space, make it easier to obtain better target classification, enhanced false- alarm rejection, and robustness to unknown statistics.

Paper Details

Date Published: 24 August 2000
PDF: 12 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396367
Show Author Affiliations
Gary F. Brendel, MIT Lincoln Lab. (United States)
Larry L. Horowitz, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 4053:
Algorithms for Synthetic Aperture Radar Imagery VII
Edmund G. Zelnio, Editor(s)

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