PS-DInSAR deformation velocity estimation by the compressive sensing

PS-DInSAR has been a tool for detecting surface micro-deformation. However, the technique is constrained by the quantity of SAR images which should be more than 30. Compressive Sensing (CS) is a new method of signal processing and allows recovering signal stably with fewer measurements. The paper applied CS to PS-DInSAR after analyzing the sparsity of data and proposed a novel method to estimate the deformation velocity with a high accuracy by using fewer SAR images. Our method will reduce the redundant data. A scene with a cone-shaped peak is designed to generate SAR images. Simulation results are presented to validate our method.