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Extensive work has been published on theoretical methods for ground moving target indication (GMTI) in synthetic aperture radar (SAR) images. The primary challenge to this problem is that SAR imaging inherently assumes a stationary scene in order to allow a long coherent processing interval, and thus moving targets that violate that assumption may be difficult to reliably detect. Recent work in this area has benefited from experiments with measured data sets, that are of high-quality but also include the measurement imperfections innate to any measured data. In many instances, sophisticated SAR-GMTI techniques have been brought to bear without necessarily employing well-known bootstrapping methods for data calibration and error correction. This leads to comparisons with algorithm baselines that are not reflective of the state of the art and to performance analysis with new algorithms that may be inaccurate or even pessimistic due to the presence of unresolved measurement errors. In this paper, we show that straightforward methods of SAR data calibration allows high-quality SAR-GMTI images to be achieved from measured data via simplistic clutter cancellation and along-track interferometry. These simple steps may serve as the basis for the testing of more advanced algorithms.
Conference Presentation
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Brian D. Rigling, Uttam Majumder, Edmund Zelnio, "Boot-strapping methods for improved SAR-GMTI," Proc. SPIE 13032, Algorithms for Synthetic Aperture Radar Imagery XXXI, 130320A (7 June 2024); https://doi.org/10.1117/12.3014323