Kriging-Based Atmospheric Phase Screen Compensation Incorporating Time-Series Similarity in Ground-Based Radar Interferometry

Abstract

Accuracy of radar interferometry is often hindered by the atmospheric phase screen (APS). To address this limitation, the geostatistical approach known as Kriging has been employed to predict APS from sparse observations for compensation purposes. In this article, we propose an enhanced Kriging approach to achieve more accurate APS predictions in ground-based (GB) radar interferometry applications. Specifically, the Kriging system is augmented with a time-series measure through correlation analysis, effectively leveraging spatiotemporal information for APS prediction. The validity of the introduced Kriging method in the APS compensation framework was tested with Ku-band GB radar datasets collected over two different mountainous sites. A comparison of this method with simple Kriging reveals a noticeable improvement in APS prediction accuracy and temporal phase stability.