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Updated: Oct 26, 2025

Generation and Coherent Control of Pulsed Quantum Frequency Combs
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Quadrature complement method for time-resolved signal frequency reconstruction.

N B Anikin1

  • 1Federal State Unitary Enterprise "Russian Federal Nuclear Center-Zababakhin All-Russia Research Institute of Technical Physics," Vasilyev Street 13, 456770 Snezhinsk, Russia.

The Review of Scientific Instruments
|August 3, 2021
PubMed
Summary
This summary is machine-generated.

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This study introduces a novel Doppler-signal processing method using integral convolutions to reduce noise and estimate Doppler signal frequency and phase. The iterative approach improves accuracy, enabling precise velocity profile reconstruction from experimental data.

Area of Science:

  • Signal Processing
  • Applied Physics
  • Biomedical Engineering

Background:

  • Doppler signal processing is crucial for various applications, including medical imaging and fluid dynamics.
  • Existing methods often struggle with noise reduction and accurate frequency estimation.
  • The need for robust algorithms to extract precise Doppler parameters is evident.

Purpose of the Study:

  • To introduce a new Doppler-signal processing method based on integral convolutions.
  • To enhance noise reduction capabilities while accurately estimating Doppler signal frequency and phase.
  • To develop an iterative procedure for improved Doppler frequency estimation and regularization.

Main Methods:

  • The method utilizes two integral convolutions with respect to the approximate Doppler phase, φ(t).

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  • It generates the first Doppler harmonic, S1‖(t), and its quadrature complement, S1⊥(t).
  • An iterative procedure is proposed for estimating Doppler frequency ωD(t) with defined transform kernels and resolution.

    • Main Results:

    • The transforms effectively reduce noise and produce the complex harmonic s1(t) = S1‖(t) + iS1⊥(t).
    • This enables accurate approximation of Doppler signal frequency, phase, and root-mean-square frequency error.
    • The iterative method converges to the Doppler frequency within the χω(t)-vicinity, with error scaling as χω(t)∼n-3/2.

    Conclusions:

    • The proposed Doppler-signal processing method offers improved noise reduction and parameter estimation.
    • It provides a new approximation for Doppler frequency and phase, crucial for accurate signal analysis.
    • The method's effectiveness is demonstrated through the reconstruction of velocity profiles from experimental Doppler signals.