Estimating gravity acceleration from an atomic gravimeter by Kalman filtering

Abstract

Abstract We present the construction of a two-state model of the atomic gravimeter and the associated Kalman recursion to estimate gravity acceleration from an atomic gravimeter. It is found that the Kalman estimator greatly improves the estimation precision in the short term by removing the white phase noise. The residual noise of the estimates follows for more than and highlights a precision of at the measuring time of a single sample, even with no seismometer correction.