InSAR phase linking enhancement by SCM refinement

This work presents a methodology to enhance phase linking, with an emphasis on SCM refinement.

This submission provides an efficient way to enhance phase linking performance in InSAR phase optimization, with an emphasis on sample coherence matrix (SCM) refinement. It builds upon existing tools and methodologies, integrating components from previously published work to enhance its capabilities. Specifically, the SCM refinement replies on TABASCO estimator (Ollila, E. and Breloy, A., 2022. Regularized Tapered Sample Covariance Matrix. IEEE Transactions on Signal Processing, 70: 2306-2320. Code link: https://github.com/esollila/Tabasco).By leveraging these resources, this implementation aims to improve phase linking performance in environments with low coherence. The incentive behind this is to exploit the inner correlation and coherence loss trend in SCM. The main advantage of the SCM refinement is the stability and low sensitivity to the variation of ensemble size.

If you use this code in your research or work, please cite the following publication:

Liang, H., Zhang, L., Li, X. and Wu, J., 2024. Coherence bias mitigation through regularized tapered coherence matrix for phase linking in decorrelated environments. ISPRS Journal of Photogrammetry and Remote Sensing.