An Improved Ionospheric Estimation Algorithm for Low-Frequency SAR Interferometry

Interferometric Synthetic Aperture Radar (InSAR) has been proven to successfully map surface deformations and monitor glacier movement. For space-borne InSAR systems working at low frequencies, the deformation measurement accuracy is strongly affected by the ionospheric effect, which can cause phase delay and lead to an obvious interference phase error. For compensation of the ionospheric effect, an improved ionospheric estimation algorithm based on the split spectrum is proposed. The theoretical basis and implementation process of the improved algorithm are described in detail in the article. In order to investigate the estimation accuracy of the proposed algorithm, simulation data with complex ionospheric changes are used and six different filtering algorithms are selected for optimization of the proposed algorithm. According to the results of the ionospheric estimation error, the improved algorithm has a smaller mean value and standard deviation than the traditional algorithm. Among the six filtering methods, the mean value and standard deviation of the ionospheric estimation result error of the Lee filtering method are much smaller than those of the original method. These results illustrate that the proposed algorithm improves the actual accuracy of ionospheric estimation and strongly certifies the effectiveness of the improved algorithm.