Progressive InSAR phase estimation

TL;DR

This paper presents a progressive phase estimation method for InSAR that enables continuous, accurate, and efficient processing of SAR image stacks, reducing data transfer needs and maintaining long-term phase accuracy.

Contribution

It introduces a novel progressive estimation scheme that performs comparably to full-covariance methods while being suitable for large-scale, continuous SAR data processing.

Findings

Comparable performance to full-covariance algorithms

Suitable for continuous processing and updating

Reduces data transfer requirements

Abstract

This paper introduces a novel scheme to progressively estimate interferometric phases from a stack of synthetic aperture radar (SAR) images. The scheme is shown to yield comparable performance to full-covariance algorithms for a realistic decorrelation scenario. The implementation is suited for continuous processing and updating of phase products, without compromising long-term phase accuracy. It also limits the requirements in terms of data transfer between archive and processing facility, a significant issue for processing large archives of SAR data.