Today, Sentinel-1A data with terrain observation with progressive scanning (TOPS) imaging mode is increasingly used in earth observation aiming at consistent monitoring of surface change and its deformation. However, due to the limited accuracy of coarse co-registration, spectral aliasing along the azimuth direction enables the presence of phase jumping in overlapping area of neighboring bursts. Although geometrical co-registration in conjunction with enhanced spectral diversity (ESD) is proven to be a feasible strategy to correct such error and has been widely used in some open source softwares (e.g. DORIS (Delft object-oriented radar interferometric software), SNAP (sentinel applications platform), ISCE (InSAR scientific computing environment)), the performance of ESD is still not satisfactory and relies strongly on spatiotemporal decorrelation. Given that decorrelation is generally quantized by interferometric coherence, this paper presents and assesses a new methodology to improve the accuracy of ESD by fully exploring the high coherent targets. Specifically, this method focuses on mitigating the spatiotemporal decorrelation in fine co-registration procedures by:(1) Selecting stable targets with moderate and high coherence using accurate coherence estimation. (2) Maximizing coherence magnitude by optimal interferometric subset chosen from Dijkstra algorithm. We compare and test this method against current favorites based on single master image and network-based enhanced spectral diversity (NESD), and the experimental results demonstrate the value of our method. It can make up for the shortage of NESD method.