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A Novel FEM with MPGA-Assisted Noise Matching Network and DC-offset Cancellation for Ultrasonic Application

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

A novel analog front-end module (FEM) featuring an auto-generated 4-6 MHz noise matching network (NMN) and DC-offset cancellation (DCOC) circuit is presented to significantly enhance the sensitivity of the ultrasonic measurement. Compared to the conventional ultrasonic FEM architectures, the proposed design achieves a higher output signal-to-noise ratio (SNR) and incorporates DC offset suppression. The NMN is automatically synthesized using a multiple population genetic algorithm (MPGA), thereby circumventing the need for complex Butterworth Van-Dyke (BVD) modeling of the ultrasonic sensor. Furthermore, a dedicated DCOC circuit is integrated into the FEM to suppress the DC noise originating from low noise amplifier (LNA) imbalance, which reduces signal distortion and mitigates baseline drift inaccuracy. The measurement results demonstrate a voltage gain of 28.3 dB and a 10.41 dB improvement in output SNR over the baseline configuration without the FEM. The ultrasonic imaging verification experiments confirm a qualitative sensing improvement, indicating the suitability of the proposed FEM for high-sensitivity ultrasonic measurement and imaging applications. © 1963-2012 IEEE.
Original languageEnglish
Article number9701711
Number of pages11
JournalIEEE Transactions on Instrumentation and Measurement
Volume75
Online published2 Apr 2026
DOIs
Publication statusPublished - 2026

Funding

This work was supported in part by the Start-Up Grant for Professor (SGP)-CityU SGP, City University of Hong Kong, under Grant 9380170; and in part by the State Key Laboratory of Radio Frequency Heterogeneous Integration (Open Scientific Research Program) under Grant KF2024013.

Research Keywords

  • DC-offset cancellation (DCOC)
  • front-end module (FEM)
  • multiple population genetic algorithm (MPGA)
  • noise matching network (NMN)
  • sensitivity
  • signal-to-noise ratio (SNR)
  • ultrasonic measurement and imaging applications

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