Abstract:

To enhance the deformation monitoring accuracy of GB-SAR in the complex slope environments of hydropower stations characterized by high steepness and humidity, a typical slope in the reservoir area of a hydropower station in Qinghai Province was selected as the test site. A rigidly fixed combined target integrating radar corner reflectors and total station prisms was designed and deployed, while both GB-SAR and a total station were set up on the stable opposite bank. The displacement of the combined target, serving as the true value, was quantitatively and precisely controlled to systematically conduct a GB-SAR accuracy validation experiment. Based on the evaluation results from high-precision benchmark data, the filtering algorithm within the GB-SAR phase signal processing chain was optimized, and an adaptive spatiotemporal filtering method incorporating terrain gradient weighting and a phase stability index was proposed. The results indicate that after algorithmic optimization, the deformation monitoring accuracy of GB-SAR for point targets in complex hydropower station slope environments is consistently improved to the submillimeter level (0.1 mm). The proposed quantitative displacement verification method and effective algorithmic optimization strategy significantly enhance the monitoring accuracy of GB-SAR in harsh environments and provide precise and reliable technical support for early warning of slope safety at hydropower stations.

Key words: ground-based synthetic aperture radar (GB-SAR), hydropower station slope, deformation monitoring, corner reflector, filtering algorithm