Noise analysis and suppression in a calibration measurement system for a moving-base gravity gradiometer

Abstract The rotating accelerometer gravity gradiometer (RAGG) is currently the only practical type of moving-base gravity gradiometer. It is carried by a vehicle along a specific survey path to measure the gravity field of a target region. RAGGs play an important role in resource exploration and auxiliary navigation. The dynamic performance of a RAGG is the key to actual gravity gradient measurement. In order to analyze the dynamic performance of a self-developed RAGG, a calibration test was conducted by mounting the RAGG on a displacement platform with a speed of 1 mm s −1 . The measurement results exhibited significant drift and impulse noise, which seriously affect the measurement accuracy and limit the application of conventional methods. In order to suppress the measurement noise of the RAGG, a Laplace distribution model of the measurement noise was established. Combined with maximum likelihood estimation, estimation of the least absolute deviation was proposed to fit and cancel the drift noise and a specific weighted median filter was designed to eliminate the impulse noise. These methods successfully reduced the root mean square error of the RAGG calibration measurement from 76 E to 31 E (where ‘E’ is a unit of gravity gradient), representing a 42% improvement compared with the conventional method and effectively enhancing the measurement accuracy of the self-developed RAGG.