Advanced Tropospheric Delay Mitigation Method Using InSAR-Based Iterative Decomposition by Considering the Statistical Characteristics of Atmospheric Turbulence

An advanced synthetic aperture radar interferometry (InSAR)-based iterative tropospheric decomposition model for more effectively mitigating both vertically stratified and turbulent delays is proposed in this article. The novelty of the model lies in two aspects: 1) incorporating turbulence variance, which characterizes the statistical properties of atmospheric turbulence, into a stochastic model when iteratively removing stratified delay and 2) taking the distance and turbulence variance as the weight factors of samples, simultaneously, in spatially interpolating turbulence. In addition, our model is implemented interferogram by interferogram, so we do not need time-series InSAR datasets. The effectiveness of the proposed method is tested and validated using a set of simulated experiments and an in-site experiment over Hawaii Island, and the experimental results show that our method can mitigate tropospheric delays efficiently and robustly.