Estimating gravity acceleration from static atomic gravimeter by Kalman filtering

TL;DR

This paper develops a Kalman filtering approach for static atomic gravimeters, significantly enhancing short-term measurement precision by effectively reducing white phase noise and achieving high accuracy over extended periods.

Contribution

It introduces a two-state model and Kalman recursion tailored for atomic gravimeters, improving gravity acceleration estimation accuracy without additional seismometer correction.

Findings

Residual noise of 0.13 muGal/√s over 100 s

Measurement precision of 0.34 muGal per sample

Kalman filter effectively reduces white phase noise

Abstract

We present the construction of the two-state model of the atomic gravimeter and the associated Kalman recursion to estimate gravity acceleration from atomic gravimeter. We find the Kalman estimator greatly improve the precision of estimates in short term by removing the white phase noise. The residual noise of the estimates follows 0.13 muGal/\sqrt{s} for up to more than 100 s and highlights a precision of 0.34 muGal at the measuring time of a single sample, even with no seismometer correction.