23 May 2013 Joint imaging and change detection for robust exploitation in interrupted SAR environments
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Abstract
Modern radar systems equipped with agile-beam technology support multiple modes of operation, including, for example, tracking, automated target recognition (ATR), and synthetic aperture radar imaging (SAR). In a multimode operating environment, the services compete for radar resources and leave gaps in the coherent collection aperture devoted to SAR imaging. Such gapped collections, referred to as interrupted SAR, typically result in significant image distortion and can substantially degrade subsequent exploitation tasks, such as change detection. In this work we present a new form of exploitation that jointly performs imaging and coherent change detection in interrupted environments. We adopt a Bayesian approach that inherently accommodates different interrupt patterns and compensates for missing data via exploitation of 1) a partially coherent model for reference-pass to mission-pass pixel transitions, and 2) the a priori notion that changes between passes are generally sparse and spatially clustered. We employ approximate message passing for computationally efficient Bayesian inference and demonstrate performance on measured and synthetic SAR data. The results demonstrate near optimal (ungapped) performance with pulse loss rates up to ∼ 50% and highlight orders of magnitude reduction in false alarm rates compared to traditional methods.
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Joshua N. Ash, "Joint imaging and change detection for robust exploitation in interrupted SAR environments", Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, 87460J (23 May 2013); doi: 10.1117/12.2019019; https://doi.org/10.1117/12.2019019
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