Modeling and Performance Evaluation of TomoSAR System Based on Reflected Signal of Beidou Navigation Satellite

TomoSAR improves the information dimension of radar image from 2D to 3D, and is widely used in elevation modeling, deformation inversion of infrastructure such as high-rise buildings, dams and mining areas, and forest vegetation biomass estimation. However, the revisiting time of traditional spaceborne TomoSAR is more than 10 days, it is difficult to monitor and forecast the sudden deformation in real time. Furthermore, most of the low-orbit satellites are deployed in the north-south direction, so the deformation measurement accuracy in the north-south direction is relatively poor. The orbit baselines in height direction of low orbit satellites are small, so the image quantity and cost of high resolution tomography processing are huge. Therefore, low orbit TomoSAR is difficult to achieve high frequency, high precision and low-cost three-dimensional deformation measurement. Although GEO SAR and MEO SAR systems have the advantages of shorter revisit period, longer observation time and larger beam coverage area theoretically, there are no satellites in orbit at present. GNSS-TomoSAR, based on the reflected signals of navigation satellites, uses the in-orbit navigation satellite as the irradiation source, and a stationary receiver is placed on the ground to receive the echo signal reflected from the scene for synthetic aperture radar tomographic processing, which can achieve high frequency, high precision and low-cost three-dimensional deformation monitoring of the scene. GNSS-TomoSAR is a relatively novel signal processing concept, which is rarely studied at home and abroad. In this paper, the signal processing model of GNSS-TomoSAR is established, the performance boundary of GNSS-TomoSAR is discussed, and the actual track of Beidou IGSO satellite is used to conduct the simulation of height inversion of point target in GNSS-TomoSAR configuration. In above, the application prospect of GNSS-TomoSAR technology is preliminarily explored, lying a foundation for GNSS-TomoSAR real data processing.