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Advanced signal processing methods for pulsed laser vibrometry.

Julien Totems1, Véronique Jolivet, Jean-Philippe Ovarlez

  • 1Onera, The French Aerospace Laboratory, Theoretical and Applied Optics Department, Chemin de la Hunière, 91761 Palaiseau Cedex, France. julien.totems@onera.fr

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Summary

Pulsed laser radar vibrometry struggles with noise. Advanced signal processing, including polypulse waveforms and time-frequency representations, significantly improves measurement accuracy in challenging conditions.

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Area of Science:

  • Optics and Photonics
  • Signal Processing
  • Vibration Measurement

Background:

  • Pulsed coherent laser radar vibrometry offers advantages over continuous wave (CW) systems but is susceptible to decorrelation noise like speckle.
  • Existing methods struggle with signal fading and noise in harsh measurement environments.

Purpose of the Study:

  • To compare different signal processing techniques for pulsed laser radar vibrometry.
  • To introduce advanced methods for mitigating noise and signal fading in vibration measurements.

Main Methods:

  • Extensive comparison of CW, pulse-pair, and polypulse laser radar emissions.
  • Development and testing of a computationally efficient maximum likelihood estimator.
  • Application of signal tracking on pseudo-time-frequency representations (TFRs).
  • Validation using simulated data and a 1.55 micrometer all-fiber vibrometer experiment with simulated vibration and speckle noise.

Main Results:

  • Advanced signal processing techniques, particularly those considering noise statistics, demonstrate superior performance.
  • The maximum likelihood estimator effectively mitigates speckle noise.
  • Pseudo-time-frequency representations aid in tracking signals under fading conditions.
  • Experimental validation confirms the benefits of the proposed methods.

Conclusions:

  • Polypulse waveforms combined with advanced signal processing offer a robust solution for laser radar vibrometry.
  • Maximum likelihood estimation and TFRs are crucial for accurate measurements in noisy environments.
  • Wider adoption of TFRs is recommended for tracking vibration-modulated signals in challenging applications.