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Calibration Curves: Linear Least Squares01:20

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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
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A Modulated Wideband Converter Model Based on Linear Algebra and Its Application to Fast Calibration.

Gilles Burel1, Anthony Fiche1, Roland Gautier1

  • 1Université de Bretagne Occidentale, Lab-STICC, CNRS, UMR 6285, 6 Avenue Le Gorgeu, 29200 Brest, France.

Sensors (Basel, Switzerland)
|October 14, 2022
PubMed
Summary

Advanced radio spectrum monitoring for IoT and smart cities is enabled by compressed sampling. The Modulated Wideband Converter (MWC) offers a practical solution, with a new linear algebra model significantly speeding up calibration.

Keywords:
compressed samplinghardware calibrationlinear algebramatrix theorymodulated wideband converterspectrum monitoring

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Computer Science

Background:

  • Advanced radio spectrum monitoring is crucial for cognitive radio, smart cities, and the Internet-of-Things (IoT).
  • High sampling rate devices for wide frequency band surveillance are prohibitively expensive.
  • Compressed sampling offers a promising solution to overcome these limitations.

Purpose of the Study:

  • To develop a new model for the Modulated Wideband Converter (MWC) based entirely on linear algebra and matrix theory.
  • To demonstrate the advantages of this linear algebra approach for MWC system development and calibration.
  • To improve the efficiency and speed of MWC system calibration.

Main Methods:

  • Developed a novel MWC model utilizing linear algebra, matrix theory, and block processing.
  • Applied signal processing concepts including filtering, modulation, and Fourier series decomposition.
  • Integrated in-flow data processing and block processing techniques.

Main Results:

  • The linear algebra-based MWC model simplifies software implementation and removes constraints of the initial model.
  • Achieved a significant speed-up in calibration computation time, exceeding a factor of 20 compared to previous methods.
  • Validated the MWC approach in real-world conditions with existing analog components.

Conclusions:

  • The linear algebra framework provides an efficient and practical foundation for MWC systems.
  • This new approach enables faster and more accessible calibration for real-world MWC applications.
  • The MWC system, enhanced by this model, is a viable solution for advanced radio spectrum monitoring in IoT and smart cities.