Underground Goaf Parameters Estimation by Cross-Iteration with InSAR Measurements

Determining the geographic location and spatial distribution of underground goaf is great significance for prevention mining subsidence hazards detection illegal mining. However, traditional techniques mainly focus on geophysical methods that are labor intensive, have low efficiency, expensive. Due to large range off-site monitoring capability interferometric synthetic aperture radar (InSAR) techniques, research based InSAR measurements has been increasing. This paper proposes a new method locating cross-iteration measurements. Firstly, functional relationship between geometric parameters line sight (LOS) deformation retrieved by constructed. Then, three initial model probability integration (PIM) determined geological conditions. Finally, used determine characterize goaf. The experimental results show average relative errors simulated experiment real 1.5% 5.1%, respectively, inverted in good agreement with values. Moreover, proposed only requires main lithology overlying rock does not depend accuracy PIM parameters. Therefore, this engineering application value lacking actual measurement data or caused