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- W2901591750 abstract "This paper presents an adjustable angular superresolution method to realize high azimuthal resolution of forward-looking area in scanning radar imaging. Firstly, the received signal in azimuth dimension is established as the convolution model of target scattering coefficient and antenna pattern. Then based on the Poisson statistic assumption, the Generalized Gaussian distribution as prior constraint is used in the maximum a posterior (MAP) method due to the adjustability of dispersion parameter. At last, how to choose suitable dispersion parameter is discussed for better superresolution performance of different scenes. The simulations and experimental results are given to verify the performance of proposed method." @default.
- W2901591750 created "2018-11-29" @default.
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- W2901591750 date "2018-07-01" @default.
- W2901591750 modified "2023-10-18" @default.
- W2901591750 title "Bayesian Superresolution Method of Forward-Looking Imaging with Generalized Gaussian Constraint" @default.
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- W2901591750 doi "https://doi.org/10.1109/igarss.2018.8518233" @default.
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