Normalized Collocation Based on Variance Component Estimate and Its Application in Multi-source Gravity Data Fusion

Aiming to address the problem of variance component inconformity between signal and noise from multi-source gravity anomalies, the variance component estimate was introduced into the least square collocation (LSC) method, while the Tikhonov normalizing method was used to address the covariance matrix singularity problem. Experiments under different error conditions were carried out and compared. Results showed that, as compared to the LSC method, the proposed method reduced the systematic error of data fusion. It showed better behaviors both in fusion precision and reliability than standard LSC.