Least square estimation of phase, frequency and PDEV

TL;DR

This paper presents a new decimation rule for PVAR estimates in Omega-preprocessing, enabling multi-tau analysis using scalar measurements, and discusses hardware requirements for high-speed computations.

Contribution

It introduces a decimation rule based on two scalars for PVAR estimates, facilitating multi-tau analysis with scalar measurements in Omega-preprocessing.

Findings

Decimation rule enables multi-tau analysis with scalar measurements.

Defines output standards and hardware requirements for high-speed processing.

Improves phase noise rejection using least square algorithms.

Abstract

The Omega-preprocessing was introduced to improve phase noise rejection by using a least square algorithm. The associated variance is the PVAR which is more efficient than MVAR to separate the different noise types. However, unlike AVAR and MVAR, the decimation of PVAR estimates for multi-tau analysis is not possible if each counter measurement is a single scalar. This paper gives a decimation rule based on two scalars, the processing blocks, for each measurement. For the Omega-preprocessing, this implies the definition of an output standard as well as hardware requirements for performing high-speed computations of the blocks.