A New Landslide Deformation Monitoring Method with Polarimetric SAR Based on Polarimetric Likelihood Ratio Test

Objectives Compared with the traditional single-polarization synthetic aperture radar(SAR), the full-polarization SAR can obtain more abundant polarimetric scattering information and describe the geometric and physical characteristics of the target more comprehensively.

Methods To make full use of the polarimetric scattering information of ground objects, we utilize the polarimetric coherence matrix used to describe distributed targets and the polarimetric likelihood ratio test (PolLRT) based on complex Wishart distribution to accurately evaluate the temporal similarity between master and slave image blocks.

Results Compared with the traditional method, this method not only considers the cross-correlation information between the same polarization, but also considers the cross-correlation information between different polarization modes, to improve the matching performance of the time series polarization information. In the real experiment, two fully polarized unmanned aerial vehicle(UAV) SAR data are used as experimental data, and the external global positioning system (GPS) deformation data is used as the reference data.

Conclusions The experimental results show that the proposed algorithm has higher deformation extraction accuracy and shows more robust deformation extraction performance under different matching window sizes.