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Proceedings Paper

Data management approach to search and rescue synthetic aperture radar
Author(s): John E. Green; George W. Rogers
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Paper Abstract

The NASA sponsored Search and Rescue Synthetic Aperture Radar (SAR) program seeks to use foliage penetrating synthetic aperture radar (SAR) to locate light plane crashes in remote areas. In addition to the hardware and pattern recognition issues, data management is recognized as a significant part of the overall problem. A single NASA/JPL AIRSAR polarimetric image in P, L, and C bands takes approximately 524 megabytes of storage. Algorithmic development efforts, as well as an eventual operational system, will likely require maintaining a large database of SAR imagery, as well as derived features and associated geographical information. The need for this much data is driven in large part by the complexity of the detection problem. A simple classification/detection algorithm does not currently seem feasible. Rather, a data driven approach that can incorporate local background characteristics as well as geographical information seems to be called for. This in turn makes data management a key issue. This paper presents a comprehensive data management framework suitable for the SAR problem, as well as other similar massive data set management problems.

Paper Details

Date Published: 23 June 1997
PDF: 7 pages
Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); doi: 10.1117/12.277111
Show Author Affiliations
John E. Green, Naval Surface Warfare Ctr. (United States)
George W. Rogers, Naval Surface Warfare Ctr. (United States)

Published in SPIE Proceedings Vol. 3069:
Automatic Target Recognition VII
Firooz A. Sadjadi, Editor(s)

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