Advances in mitigating InSAR non-closure phase bias: A refined processing approach

Interferometric synthetic aperture radar (InSAR) phase bias, most commonly observed in short-term, multilooked interferograms, can significantly impact the accuracy of ground displacement measurements, particularly in regions with vegetation or temporal decorrelation. While phase bias can largely be corrected using phase linking methods, these approaches are computationally intensive and ineffective for pixels with coherence limited to very short time intervals. This paper aims to consolidate our empirical correction algorithm for mitigating phase bias in InSAR data, demonstrating its application across three diverse study areas: the Azores in Portugal, Campi Flegrei in Italy, and Tien Shan in China. Our method estimates bias terms using only short-term wrapped interferograms and applies these terms to correct any desired interferograms. The algorithm also addresses gaps and missing interferograms within time-series data by incorporating temporal smoothing constraints, which minimize differences between estimated bias terms over time. Additionally, the study examines the temporal and spatial behavior of the calibration parameters and explores the choice of long-term interferograms for their estimation. Validation against a phase linking approach shows that our phase bias correction algorithm effectively reduces phase bias, achieving close alignment with the benchmark results. This work contributes a robust framework for correcting short-term interferograms, leading to improved InSAR velocity estimates.