Dynamic Data Processing Method of Gravity Gradiometer Based on Equivalent Source

Abstract

The gravity gradiometer is an instrument that continuously measures the small gravity gradient changes on the earth's surface. The actual output signal of the system contains a lot of noise, and the signal-to-noise ratio is extremely low due to the limitations of the process and performance level of the core sensitive element accelerometer, and the installation errors of multiple links. In order to effectively extract the real gravity gradient signal from the strong noise, a gravity gradient noise reduction method based on the equivalent source model is proposed by using the basic principle that the earth's gravity field is a conservative force field. First, according to the relationship between the rectangular prism and the gravity gradient, the analytical model of the equivalent source is derived, and the regression equation of the equivalent source is established. Aiming at the ill conditioned problem of regression operators, Tikhonov regularization method is proposed, and the optimal regularization parameters are determined by L-curve method, which can reduce the noise of gravity gradient measurement by an order of magnitude in simulation. Using this method to process the measured data of the shipborne test, the results show that this method has an obvious effect on suppressing the dynamic measurement noise of the gravity gradiometer, and can reduce the internal coincidence mean square error of the horizontal tensor gravity gradient measurement signal by 58%, which is of engineering significance.