Identification of Clock Ensemble Noise Parameters Using Differential Measurement Analysis

TL;DR

This paper develops methods to identify unknown noise parameters of atomic clock ensembles using differential phase measurements, validated on simulated and real data.

Contribution

It introduces two novel identification methods for estimating clock noise parameters from differential measurements in atomic ensembles.

Findings

Accurate estimation of white frequency and random walk noise variances.

Effective identification of clock drift and measurement noise covariance.

Validation on both simulated and real atomic clock data.

Abstract

The paper addresses the critical problem of identifying unknown parameters of an atomic clock ensemble. The ensemble model is considered as a set of individual clock models, where each clock is described by a second-order linear stochastic state-space model. The paper presents identification procedure for model unknown parameters based solely on the availability of differential measurements - that is, the measured pairwise phase differences between a designated pivot clock and all other clocks within the ensemble. Specifically, each clock model is defined by the following set of unknown parameters: the variances characterizing the white frequency noise and random walk frequency noise, the drift, and the (co)variance of the measurement noise. Two distinct identification methods are designed to estimate the unknown clock model parameters. The accuracy of the identified sets of parameters are demonstrated on a simulation scenario/real data combining atomic H-maser (AHM) clocks.