Research on GB-SAR slope deformation geocoding method based on Bayes theorem

In recent years, the ground based deformation monitoring radar (GB-SAR), as an emerging remote sensing deformation monitoring technology equipment, has become a research hotspot in the field of open pit mine slope safety and landslide geohazard prevention and control. In this paper, for the fuzzy problem of spatial localization of pixel units in the superimposed mask area of radar image, the Bayesian statistical framework is introduced into the spatial geographic coding of foundation deformation monitoring radar for the first time, and the maximum a posteriori probability function model is established on the basis of the incidence angle of the target of the slope feature and the elevation angle of the antenna's vertical direction map, so as to realize the three-dimensional visualization of landslide deformation hazardous areas, and to give full play to the technological support of the early warning of landslide disaster by foundation deformation monitoring radar.
First introduction of Bayesian statistical framework into spatial geocoding of GB-SAR to model the maximum a posteriori probability function.
Realization of three-dimensional visualization and identification of landslide deformation hazard areas.