Laser Doppler Velocimetry for Joint Measurements of Acoustic and Mean Flow Velocities : LMS-based Algorithm and CRB Calculation

TL;DR

This paper introduces an LMS-based algorithm for accurately estimating both acoustic and mean flow velocities from LDV measurements, even in disturbed acoustic fields, and validates it against the CRB through simulations.

Contribution

It proposes a novel LMS-based joint estimation algorithm for acoustic and mean flow velocities in LDV measurements, along with CRB analysis and validation.

Findings

The LMS algorithm accurately estimates velocities in simulations.

The CRB provides a theoretical lower bound for estimator variance.

Simulation results validate the effectiveness of the proposed estimator.

Abstract

This paper presents a least mean square (LMS) algorithm for the joint estimation of acoustic and mean flow velocities from laser doppler velocimetry (LDV) measurements. The usual algorithms used for measuring with LDV purely acoustic velocity or mean flow velocity may not be used when the acoustic field is disturbed by a mean flow component. The LMS-based algorithm allows accurate estimations of both acoustic and mean flow velocities. The Cram\'er-Rao bound (CRB) of the associated problem is determined. The variance of the estimators of both acoustic and mean flow velocities is also given. Simulation results of this algorithm are compared with the CRB and the comparison leads to validate this estimator.