In ultra-wideband (UWB) breast imaging, it has been shown that benign and malignant masses, which usually possess remarkable architectural differences, could be distinguished by exploiting their morphology-dependent microwave backscatter. The complex natural resonances (CNRs) of the backscatter signature can be derived from the late-time target response, where the damping factors vary with the border profiles of lesions. As an extension to our previous work (Chen et al. 2008), here we investigate the potential advantage of multiple-input multiple-output (MIMO) radars to enhance the resonance scattering phenomenon in tissue differentiation. Based on the observed damping factors and the receiver operating characteristics (ROC) at different classifiers, which correspond to various diversity paths in the MIMO radar system, the selection combining fusion scheme is proposed for robust lesion classification. We also provide numerical examples to demonstrate the efficacy of the proposed imaging technique.
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