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Proceedings Paper

Detection/tracking of moving targets with synthetic aperture radars
Author(s): Gregory E. Newstadt; Edmund Zelnio; Leroy Gorham; Alfred O. Hero
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Paper Abstract

In this work, the problem of detecting and tracking targets with synthetic aperture radars is considered. A novel approach in which prior knowledge on target motion is assumed to be known for small patches within the field of view. Probability densities are derived as priors on the moving target signature within backprojected SAR images, based on the work of Jao.1 Furthermore, detection and tracking algorithms are presented to take advantage of the derived prior densities. It was found that pure detection suffered from a high false alarm rate as the number of targets in the scene increased. Thus, tracking algorithms were implemented through a particle filter based on the Joint Multi-Target Probability Density (JMPD) particle filter2 and the unscented Kalman filter (UKF)3 that could be used in a track-before-detect scenario. It was found that the PF was superior than the UKF, and was able to track 5 targets at 0.1 second intervals with a tracking error of 0.20 ± 1.61m (95% confidence interval).

Paper Details

Date Published: 19 April 2010
PDF: 10 pages
Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990I (19 April 2010); doi: 10.1117/12.850345
Show Author Affiliations
Gregory E. Newstadt, Univ. of Michigan (United States)
Edmund Zelnio, Air Force Research Lab. (United States)
Leroy Gorham, Air Force Research Lab. (United States)
Alfred O. Hero, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 7699:
Algorithms for Synthetic Aperture Radar Imagery XVII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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