Estimating gravity acceleration from an atomic gravimeter by Kalman filtering

¹ School of Science, Shenyang University of Technology - Shenyang, Liaoning 110870, China
² Hefei National Research Center for Physical Sciences at the Microscale and Department of Modern Physics, University of Science and Technology of China - Hefei, Anhui 230026, China
³ Shanghai Branch, CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China - Shanghai 201315, China
⁴ Shanghai Research Center for Quantum Sciences - Shanghai 201315, China
⁵ Key Laboratory for Quantum Optics, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences - Shanghai 201800, China

^(a) E-mail: bnjiang@siom.ac.cn (corresponding author)

Received: 3 August 2022
Accepted: 18 November 2022

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.