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Bayesian Angular Superresolution Algorithm for Real-Aperture Imaging in Forward-Looking Radar
2015
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In real aperture imaging, the limited azimuth angular resolution seriously restricts the applications of this imaging system. This report presents a maximum a posteriori (MAP) approach based on the Bayesian framework for high angular resolution of real aperture radar. First, Rayleigh statistic and the l q norm (for 0 < q ≤ 1) sparse constraint are considered to express the clutter property and target scattering coefficient distribution, respectively. Then, the MAP objective function is
doi:10.3390/info6040650
fatcat:xsjrjeta7rfgfje6fuec265orq