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.