Postprocessing Compensation for Rotating Accelerometer Gravity Gradiometer Using Linear Motion Error Model Coefficient Calibration Method

Abstract

Motion errors pose a significant challenge to moving-base gravity gradient measurement applications. To eliminate those errors, model-based compensation methods are commonly employed. However, those compensation results are strongly influenced by the motion error model correctness. This article proposes a postprocessing compensation method, which can solve that problem, for the rotating accelerometer gravity gradiometer (RAGG). Two experiments are carefully designed to validate the different components of the linear motion error model. Using a six-degree-of-freedom (6-DOF) platform, sinusoidal excitations are employed for motion error coefficients calibration. The experimental results show that the R-squared value of the fitting ( ${R} ^{2}$ ) exceeded 0.995, confirming the accuracy of the RAGG linear motion error coefficients calibration. Additionally, using the calibrated motion error coefficients, an aircraft motion excitation is also applied on the RAGG for postprocessing compensation. The compensated outputs indicate that the motion errors can be reduced from the micro-g ( $\mu $ g) level to the order of nano-g (ng). The power spectral density (PSD) of the results after compensation show an excellent accordance with those of the RAGG self-noise in static measurement. These results provide a guidance for noise reduction and motion error compensation in RAGG systems.