In the field of ultra-wideband (UWB) multi-input multi-output (MIMO) imaging, it is difficult to recognize targets, especially weak targets, in the high grating lobes environment. To solve this problem, in this paper, an adaptive sub-band sub-aperture coherence factor (ASBSA-CF) algorithm is proposed based on sub-band sub-aperture (SBSA) image data. First, we establish the objective function by using the maximum inter-class variance (OTSU) method. Then, particle swarm optimization (PSO) algorithm is applied to adaptively choose the number of sub-bands and sub-apertures of SBSA image data. Finally, simulation verifies that ASBSA-CF can optimally achieve the compromise between weak targets and grating lobes suppression.