Knowledge-Aided Adaptive Gradient Test for Radar Targets in Correlated Compound Gaussian Sea Clutter With Lognormal Texture | IEEE Journals & Magazine | IEEE Xplore

Knowledge-Aided Adaptive Gradient Test for Radar Targets in Correlated Compound Gaussian Sea Clutter With Lognormal Texture


Abstract:

This letter deals with the knowledge-aided adaptive detection problem of radar targets in nonhomogeneous correlated compound Gaussian sea clutter. The lognormal distribut...Show More

Abstract:

This letter deals with the knowledge-aided adaptive detection problem of radar targets in nonhomogeneous correlated compound Gaussian sea clutter. The lognormal distribution is used as the prior distribution of the clutter texture to match the non-Gaussianity of sea clutter. In addition, in order to ensure the estimation accuracy of the covariance matrix structure of sea clutter, a convex combination estimator (CCE) is proposed by jointly exploiting the prior information and the current secondary data. Then, a knowledge-aided adaptive detector is designed on the basis of the complex parameter Gradient test and the CCE. Numerical experiments verify the effectiveness of the proposed CCE and adaptive detector in comparison with their counterparts, respectively.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 20)
Article Sequence Number: 3509105
Date of Publication: 17 October 2023

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