Millimeter-wave (MMW) imaging is becoming an important option in many sensing applications. However, the resulting images are often plagued with artifacts caused by complex target scenarios such as concave structures, hampering applications where precise recognition is emphasized. It has been shown that existing imaging techniques can effectively resolve this issue by considering the multi-reflection propagation process in the forward model of the inverse problem. But the accuracy of such method still depends on the precise separation of reflected signals exhibiting different number of interactions with the target surfaces. In this article, an improved imaging technique based on circular polarizations is proposed for accurate imaging of concave objects. By utilizing circular polarized measurements, the received signal can be divided into odd and even number of reflection times. Then, an iterative reconstruction technique is introduced to automatically separate signal components and reconstruct precise contours of the concave surfaces. Furthermore, a strict observation angle boundary model is derived based on methods of the stationary phase to correct the image deformation of edges existing in previous algorithms. Both numerical and experimental results synthesized from 6∼18 GHz dual-polarized measurements are used to demonstrate the improved accuracy and automation of the proposed method.