The widespread deployment of mmWave communication systems is an unstoppable trend, but its success will heavily rely on well-designed transceivers to combat the severe propagation loss. To acquire the accurate channel state information (CSI) so that the transceiver design can be facilitated, in this paper, we provide a new time-domain channel estimation scheme for hybrid mmWave massive multiple-input multiple-output (mMIMO) systems. In addition to utilizing the well-known angular sparsity, the delay-domain sparsity will also be exploited to accomplish the channel estimation with satisfactory accuracy yet affordable complexity. The successful combination of these two types of sparsity is attributed to a judiciously designed training pattern. Thanks to our innovative exploitation of the double sparsity, a satisfactory performance can be achieved together with largely reduced training overhead, storage demand, and computational complexity.