Improving Distributed Scatterer Phase Estimation Using a Refined Coherence Bias Correction Method

Distributed scatterers (DSs) should be included in multitemporal interferometric synthetic aperture radar to improve the spatial density and quality of monitoring points. As a key step, phase estimation can significantly reduce the decorrelation of DSs by exploiting all available interferograms. The current phase estimation algorithms are known to be affected by the coherence bias. In this study, we propose an improved DS phase estimation approach, which uses a refined coherence bias correction algorithm. To demonstrate the effectiveness of the proposed approach, we apply it over 50 simulated synthetic aperture radar images. The coherence bias can be significantly reduced by the proposed approach, including an average coherence bias reduction of more than 35% over the existing bias correction algorithm. The reconstructed phase series obtained by the proposed approach have higher accuracy than the current methods.