Complex-valued self-organizing map clustering using complex inner product in active millimeter-wave imaging

Millimeter-wave imaging is suitable for security systems because of its ability to detect nonmetallic threats concealed under clothes. In this paper, we propose an active millimeter-wave imaging system using a complex-valued self-organizing map (CSOM) that realizes adaptive clustering of complex-valued texture in space and frequency domain to visualize targets. In the choice of winners in the CSOM, we also propose complex-valued inner-product metric to enhance the coherent merit in active imaging as well as to reduce the glaring and speckle distortion. We compare the performance obtained for the proposed method with that of Euclidean method.