In this paper, a 3D high-resolution imaging method based on compressive sensing reconstruction theory is proposed for Frequency Modulated Continuous Wave (FMCW) Colocated Multiple Input Multiple Output (MIMO) radar. For the array signals obtained by Time Division Multiple access MIMO radars, the block compressed sensing (BCS) method based on antenna spatial layout was adopted. In addition, a three-dimensional Constant false alarm Rate (3D-CFAR) filter was designed to reduce the influence of clutter signals on the quality of reconstructed signals, and a correlation smoothing method was designed to eliminate the reconstruction errors between different blocks. The proposed algorithm can achieve high-resolution imaging of complex targets at a low sampling ratio and avoid the problems of algorithm complexity and hardware resource occupation in traditional compressed sensing reconstruction. Simulation and experiment prove its feasibility and practicability. Compared with other imaging methods, the high-resolution imaging effect of the proposed algorithm is comparable to that of Synthetic Aperture Radar (SAR). The simulation results show that when the compressed sampling ratio is 0.6, the signal-to-clutter ratio of the target imaging has reached the level of the original target, and the target structural similarity index has reached 80%, which realizes the ideal imaging effect. The algorithm has practicability in the engineering field and is expected to be widely used in target detection and recognition of millimeter wave radar.