Comparison of density and positioning accuracy of PS extracted from super-resolution PSI with those from traditional PSI

In the application of persistent scatterer interferometry (PSI), deformation information is extracted from persistent scatterer (PS) points. Thus, the density and position of PS points are critical for PSI. To increase the PS density, a time-series In-SAR chain termed as "super-resolution persistent scatterer interferometry" (SR-PSI) is proposed. In this study, we investigate certain important properties of SR-PSI. First, we review the main workflow and dataflow of SR-PSI. It is shown that in the implementation of the Capon algorithm, the diagonal loading (DL) approach should be only used when the condition number of the covariance matrix is sufficiently high to reduce the discontinuities between the joint images. We then discuss the density and positioning accuracy of PS when compared with traditional PSI. The theory and experimental results indicate that SR-PSI can increase the PS density in urban areas. However, it is ineffective for the rural areas, which should be an important consideration for the engineering application of SR-PSI. Furthermore, we validate that the positioning accuracy of PS can be improved by SR-PSI via simulations.