Improving phase unwrapping techniques by the use of local frequency estimates

In multipass spaceborne synthetic aperture radar (SAR) interferometry, the two acquisitions often present low correlation levels and very noisy phase measurements that are incompatible with automatic phase unwrapping. Instead of dealing with many residues due to erroneous-wrapped phase differences, the authors propose to use the local frequency as measured by a spectral analysis algorithm presented in a previous paper, E. Trouve et al. (1996). For this purpose, the authors present two conventional unwrapping algorithms, one local and the other global, which they revisit to benefit from the robust focal frequency estimates. For a local approach based on path-following techniques, they use the frequency estimates in a slope-compensated filter that extend the complex averaging up to a sufficient number of looks to eliminate residues due to the noise. Then they connect residues due to noninterferometric features along mask components resulting from the detection of layovers and uncorrelated areas. For a global approach, such as the weighted least-squares methods, they demonstrate that the use of noisy discrete phase gradient leads to a biased solution. To avoid this drawback, they propose to use the local frequency estimate and associated measure of confidence as phase gradient and weight. Results are presented on both topographic and differential interferograms obtained from the ERS-1 European radar satellite over various landscapes and the displacement field of the Landers 1992 earthquake