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Proceedings Paper

Kronecker STAP and SAR GMTI
Author(s): Kristjan H. Greenewald; Edmund G. Zelnio; Alfred O. Hero
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Paper Abstract

As a high resolution radar imaging modality, SAR detects and localizes non-moving targets accurately, giving it an advantage over lower resolution GMTI radars. Moving target detection is more challenging due to target smearing and masking by clutter. Space-time adaptive processing (STAP) is often used on multiantenna SAR to remove the stationary clutter and enhance the moving targets. In (Greenewald et al., 2016),1 it was shown that the performance of STAP can be improved by modeling the clutter covariance as a space vs. time Kronecker product with low rank factors, providing robustness and reducing the number of training samples required. In this work, we present a massively parallel algorithm for implementing Kronecker product STAP, enabling application to very large SAR datasets (such as the 2006 Gotcha data collection) using GPUs. Finally, we develop an extension of Kronecker STAP that uses information from multiple passes to improve moving target detection.

Paper Details

Date Published: 14 May 2016
PDF: 12 pages
Proc. SPIE 9843, Algorithms for Synthetic Aperture Radar Imagery XXIII, 98430E (14 May 2016); doi: 10.1117/12.2223896
Show Author Affiliations
Kristjan H. Greenewald, Univ. of Michigan (United States)
Edmund G. Zelnio, Air Force Research Lab. (United States)
Alfred O. Hero, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 9843:
Algorithms for Synthetic Aperture Radar Imagery XXIII
Edmund Zelnio; Frederick D. Garber, Editor(s)

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