Imaging of the human body using ultra-wideband (UWB) radar for security applications has numerous advantages over other approaches. Recently, low-cost radar systems have been intensively studied for this purpose, employing Doppler interferometry technology to image a single human target. The technique, however, has limitations when there is more than one target person in the scene. To resolve this problem, we combined the Doppler interferometry algorithm with adaptive array processing. This approach enables the separation of multiple human targets with the help of a clustering algorithm. We applied the proposed method to simulated data and demonstrated that it could separate multiple human echoes with a root-mean-square error of 4.3 cm, which makes the accuracy more than three times higher than that of the conventional method.