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Bayesian Superresolution Method of Forward-Looking Imaging with Generalized Gaussian Constraint | IEEE Conference Publication | IEEE Xplore

Bayesian Superresolution Method of Forward-Looking Imaging with Generalized Gaussian Constraint

Publisher: IEEE

Abstract:

This paper presents an adjustable angular superresolution method to realize high azimuthal resolution of forward-looking area in scanning radar imaging. Firstly, the rece...View more

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.
Date of Conference: 22-27 July 2018
Date Added to IEEE Xplore: 04 November 2018
ISBN Information:

ISSN Information:

Publisher: IEEE
Conference Location: Valencia, Spain

References

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