PROPELLER has been applied to suppress respiratory motion for free-breathing abdomen imaging but the results are often unsatisfactory with existing weighting mechanisms. In this study, a novel adaptive weighting method is proposed to maximize the respiratory motion suppression without using a fallible reference blade. First, mutual information is used to measure the motion correlation across different blades. Second, principal components analysis is applied to adaptively reject/keep the acquired data by assigning proper weights to all blades. Our experiments show that the proposed method can provide abdominal images with less blurring and less partial volume artifacts compare to the conventional PROPELLER.