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Optimal Rayleigh Approximation of the K-Distribution via the Kullback–Leibler Divergence | IEEE Journals & Magazine | IEEE Xplore

Optimal Rayleigh Approximation of the K-Distribution via the Kullback–Leibler Divergence


Abstract:

Understanding the validity of distributional approximations is important in radar signal processing. This is certainly exemplified in the context of target detection with...Show More

Abstract:

Understanding the validity of distributional approximations is important in radar signal processing. This is certainly exemplified in the context of target detection with X-band maritime surveillance radar. This is due to the fact that if the underlying clutter amplitude model can be assumed to be Rayleigh distributed, then there is a large class of detection processes with the constant false alarm rate property that can be applied. This paper examines the Rayleigh approximation of the K-distribution, since the latter is a popular model in X-band maritime surveillance radar. With an application of ideas from information theory, and in particular the Kullback-Leibler divergence, it is possible to derive the optimal Rayleigh approximation for any given K-distribution. Consequently bounds are derived to measure this approximation. These bounds reveal a necessary interaction between the K-distribution parameters to achieve a good Rayleigh approximation. Some numerical results are included to provide a practical assessment of the approximation.
Published in: IEEE Signal Processing Letters ( Volume: 23, Issue: 8, August 2016)
Page(s): 1067 - 1070
Date of Publication: 21 June 2016

ISSN Information:


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