To address the problem that the clutter suppression performance of a multichannel synthetic aperture radar ground moving target indicator(SAR-GMTI) system is reduced due to non-uniform clutter in a complex geographical scene
we propose a multichannel SAR-GMTI clutter suppression method assisted by Range-Doppler-Band three dimension adaptive weighted penalty markov random field(3D-AWP-MRF) classification. Firstly
an adaptive weighted penalty function is constructed using the markov properties of the feature types in the Range-Doppler-Band 3D SAR image domain. Spatial distance
inter-class Fisher distance
local roughness distance
and gradient direction distance are included. Subsequently
in the Bayesian framework
iterated conditional mode(ICM) algorithm is used to solve the maximum posterior probability of the feature type of the Range-Doppler unit
so as to accurately classify the multiband SAR images. Then
the image classification results are obtained by image morphology operation. Finally
the clutter covariance matrix is estimated separately for each closed region
and adaptive clutter suppression processing is performed. Compared with the traditional method
the proposed method not only can improve the suppression performance about 10~15 dB for the strong clutter in undulating areas
but also reduce the output signal power loss about 2.5dB of the moving targets in flat areas.
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