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15 April 2008 Three-dimensional sparse-aperture moving-target imaging
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If a target's motion can be determined, the problem of reconstructing a 3D target image becomes a sparse-aperture imaging problem. That is, the data lies on a random trajectory in k-space, which constitutes a sparse data collection that yields very low-resolution images if backprojection or other standard imaging techniques are used. This paper investigates two moving-target imaging algorithms: the first is a greedy algorithm based on the CLEAN technique, and the second is a version of Basis Pursuit Denoising. The two imaging algorithms are compared for a realistic moving-target motion history applied to a Xpatch-generated backhoe data set.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Matthew Ferrara, Julie Jackson, and Mark Stuff "Three-dimensional sparse-aperture moving-target imaging", Proc. SPIE 6970, Algorithms for Synthetic Aperture Radar Imagery XV, 697006 (15 April 2008);


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