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Journal of Electronic Imaging

Persistence modeling of angularly dependent synthetic aperture radar imagery
Author(s): Scott Papson; Ram M. Narayanan
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Paper Abstract

An image persistence framework is developed to analyze azimuthally varying synthetic aperture radar (SAR) data. The model focuses on cases containing rich aspect data from a single depression angle. The goal is to replace the data's intrinsic viewing geometry dependencies with target-specific dependencies. Both direct mapping functions and cost functions are presented for data transformation. An intensity-only mapping function is realized to illustrate the persistence model in terms of a canonical example, visualization, and classification. The limitations of an intensity-only mapping function are also discussed. Because the new image-space output from the persistence model is closely tied to the radio frequency (RF) characteristics of two different targets and not to the collection geometry, it shows promise for integration into various automated target recognition (ATR) algorithms. Target classification potential was tested using the MSTAR database and simplified template matching schemes. The intensity-only transformation function permits a very low number of persistence images to represent the general RF target characteristics of an assortment of vehicles. The ability to represent target characteristics with relatively low resources could also be beneficial in ATR applications. Overall, the persistence framework shows strong potential as a new tool that can be used in the analysis of multiaspect SAR images.

Paper Details

Date Published: 1 July 2008
PDF: 9 pages
J. Electron. Imaging. 17(3) 033013 doi: 10.1117/1.2952592
Published in: Journal of Electronic Imaging Volume 17, Issue 3
Show Author Affiliations
Scott Papson, The Pennsylvania State Univ. (United States)
Ram M. Narayanan, The Pennsylvania State Univ. (United States)


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