Paper
18 April 2010 Detection/tracking of moving targets with synthetic aperture radars
Author Affiliations +
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).
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory E. Newstadt, Edmund Zelnio, Leroy Gorham, and Alfred O. Hero III "Detection/tracking of moving targets with synthetic aperture radars", Proc. SPIE 7699, Algorithms for Synthetic Aperture Radar Imagery XVII, 76990I (18 April 2010); https://doi.org/10.1117/12.850345
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CITATIONS
Cited by 8 scholarly publications and 1 patent.
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KEYWORDS
Target detection

Detection and tracking algorithms

Synthetic aperture radar

Particle filters

Data modeling

Filtering (signal processing)

Roads

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