Interferometric Synthetic Aperture Radar Phase Composition Analysis and Simulation

The acquisition of data is attracting attention, and especially in the big data environment, it is important to obtain data with accurate values. The acquisition of real data is limited by the real-time changes of uncontrollable factors such as the noise of the synthetic aperture radar (SAR) sensor itself and the environment, which make the data acquired at different times slightly different and are not conducive to our experiments such as the cross-validation of data. Thus, simulated data is often used for various validation tests. On the basis of the mathematical model of interferometry synthetic aperture radar (InSAR), we can simulate the InSAR data relatively easily and the simulated data have accurate values. The study of mathematical models is the basis for the improvement of InSAR sensors. For the complex hybrid model of InSAR, in this paper, we examine the phase components of InSAR and analyze the phase models one by one. Matrix Laboratory (MATLAB) has powerful mathematical and graphical processing capabilities; thus, in this paper, we use MATLAB to simulate the data. In addition, we combine the real geographic data structure, simulation, and fusion of a region of real data to verify the feasibility of the data simulation in this paper, which provides a basis for subsequent research or InSAR sensor upgrades.