Analysis of Downward Continuation Model of Airborne Gravity Based on Comprehensive Semi-parametric Kernel Estimation and Regularization Method

In the process of downward continuation(DWC) of airborne gravity, the model error caused by discretization and systematic error in gravity data is expressed by non⁃parametric components. This paper proposes an inverse Poisson integral DWC method based on regularization method and semi⁃parametric kernel estimation, establishes gravity DWC model based on semi⁃parametric kernel estimation method without external data, reduces the ill⁃conditioned influence of the design matrix after Poisson integral discretization and introduces regularization method. It calculates the simulated airborne gravity anomaly based on the EGM2008 model and performs the simulation experiment using linear term and periodic term systematic error. The simulation experiment and the measured gravity anomaly data in the United States show the effectiveness of the proposed method in improving the ill⁃conditioned and separation system errors. The results show that the proposed method can effectively separate systematic errors and has high precision when there is no external data.