Publication:
Analog lock-in amplifier design using subsampling for accuracy enhancement in GMI sensor applications

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Date

2023

Director

Publisher

MDPI
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107258RB-C32/ES/

Abstract

A frequency downscaling technique for enhancing the accuracy of analog lock-in amplifier (LIA) architectures in giant magneto-impedance (GMI) sensor applications is presented in this paper. As a proof of concept, the proposed method is applied to two different LIA topologies using, respectively, analog and switching-based multiplication for phase-sensitive detection. Specifically, the operation frequency of both the input and the reference signals of the phase-sensitive detector (PSD) block of the LIA is reduced through a subsampling process using sample-and-hold (SH) circuits. A frequency downscaling from 200 kHz, which is the optimal operating frequency of the employed GMI sensor, to 1 kHz has been performed. In this way, the proposed technique exploits the inherent advantages of analog signal multiplication at low frequencies, while the principle of operation of the PSD remains unaltered. The circuits were assembled using discrete components, and the frequency downscaling proposal was experimentally validated by comparing the measurement accuracy with the equivalent conventional circuits. The experimental results revealed that the error in the signal magnitude measurements was reduced by a factor of 8 in the case of the analog multipliers and by a factor of 21 when a PSD based on switched multipliers was used. The error in-phase detection using a two-phase LIA was also reduced by more than 25%.

Keywords

Lock-in amplifier, Phase-sensitive detector, GMI sensor, Subsampling, Sample-and-hold

Department

Ciencias / Zientziak / Institute of Smart Cities - ISC / Institute for Advanced Materials and Mathematics - INAMAT2

Faculty/School

Degree

Doctorate program

Editor version

Funding entities

This work has been supported by Grant PID2019-107258RB-C32 funded by the Spanish Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033), and by the project PJUPNA2005 funded by the Public University of Navarre.

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.

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