23 June 1997 Data management approach to search and rescue synthetic aperture radar
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
John E. Green, John E. Green, George W. Rogers, George W. Rogers, } "Data management approach to search and rescue synthetic aperture radar", Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); doi: 10.1117/12.277111; https://doi.org/10.1117/12.277111
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