The launch of the wide-swath SAR missions with short repeat-pass cycles, such as Sentinel-1, will soon lead to an unprecedented large InSAR data archive. Time-series analysis on the rapidly growing data will thus become computationally demanding for a systematic monitoring of earth surface deformation. As the state-of-the-art approach in InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the upcoming big data; an aspect to which limited attention has been dedicated so far. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing with negligible performance loss compared to the Cramér-Rao Lower Bound. The performance of the proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to the real C- and L-band data is ongoing and will be presented in the final paper.     «

The launch of the wide-swath SAR missions with short repeat-pass cycles, such as Sentinel-1, will soon lead to an unprecedented large InSAR data archive. Time-series analysis on the rapidly growing data will thus become computationally demanding for a systematic monitoring of earth surface deformation. As the state-of-the-art approach in InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the upcoming big data;...     »