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Proceedings Paper

Diffusion maps and radar data analysis
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Paper Abstract

Understanding and organizing data, in particular understanding the key modes of variation in the data, is a first step toward exploiting and evaluating sensor phenomenology. Spectral theory and manifold learning methods have been recently shown to offer sever powerful tools for many parts of the exploitation problem. We will describe the method of diffusion maps and give some examples with radar (backhoe data dome) data. The so-called diffusion coordinates are kernel based dimensionality reduction techniques that can, for example, organize random data and yield explicit insight into the type and relative importance of the data variation. We will provide sufficient background for others to adopt these tools and apply them to other aspects of exploitation and evaluation.

Paper Details

Date Published: 7 May 2007
PDF: 12 pages
Proc. SPIE 6568, Algorithms for Synthetic Aperture Radar Imagery XIV, 65680X (7 May 2007); doi: 10.1117/12.731459
Show Author Affiliations
Y. S. Bhat, Univ. of Minnesota (United States)
Gregory Arnold, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 6568:
Algorithms for Synthetic Aperture Radar Imagery XIV
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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