article

The PS-InSAR analysis method is a technique that utilizes persistent scatter in SAR images and performs image analysis by interfering with 25 or more slave images in a master image. Determining the accuracy of the above algorithm is the denser between images, the higher the coherence, the more accurate the image is. Therefore, the Minimum Spanning Tree (MST) algorithm is used to find the optimum coherence by considering the temporal, spatial, and coherence of each image rather than Star graph, which interferes with the rest of the slave images in one master image. However if MST algorithms are carried out considering the high coherence between images, the high coherence interference pairs can be connected, but the higher the number and size of images, the higher the processing speed. In this study, MST algorithms were carried out in consideration of the basic information of images, spatial baseline, and temporal baseline, without any imaging processing. In order to verify this, a three-dimensional regression analysis was conducted, taking into account the correlation of spatial baseline, temporal baseline, and coherence. Also, a new MST algorithm was performed taking into account the weights derived from the above analysis. The results showed that a high coherence of 98.5% over the previous analysis was achieved in a short time and an increase of about 120% over the Star graph.