A New Optimization Selection Method of Common Master Image for PSInSAR Interferometry

In PSInSAR technique which based on temporal analysis, the optimization selection of master image can directly affects the subsequent results of the deformation phase extraction and subsidence information calculation. In this paper, considering the different interferometric decoherence factors of image pairs such as space vertical baseline, temporal baseline and Doppler centroid frequency, calculate the three decoherence factors in numerical measure. three factors are mapped to three-dimensional space and regarded as three particles, three particle considered one object, through the comprehensive study of centroid of the object to measure the impact of three particles on the coherence between the images, and then build a new master image optimization selection model Respectively, using the proposed model and the integrated correlation coefficient model to take master image selection experiment for 28 scene images acquired by ENVISAT ASAR from 2003 to 2009 over Beijing. To verify the master image selection by different model, separately use the two selected result to interfere with the other images, take the interferogrames generated and mean correlation coefficient as quantitative evaluation. The results show: Compared with integrated correlation coefficient model, the master image selected by this method proposed to is more reasonable, and the overall interference between other auxiliary images is better, meanwhile, and the model proposed is stable.