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Area of Science:

  • Signal Processing
  • Electrical Engineering
  • Communications

Background:

  • Phase difference estimation is crucial for many applications.
  • Incoherent sampling (IS) degrades the precision of traditional estimation methods.
  • Spectral superposition in real signals further complicates estimation.

Purpose of the Study:

  • To develop a novel estimator for phase difference estimation under incoherent sampling.
  • To address the challenges posed by spectral superposition of real signals.
  • To improve the accuracy and robustness of phase difference estimation.

Main Methods:

  • A novel estimator based on signal modulation and the discrete Fourier transform (DFT) was developed.
  • The method utilizes four DFT samples of modulated signals for phase difference calculation.
  • Frequency estimation is incorporated to enhance phase difference retrieval.

Main Results:

  • The proposed method demonstrates validity through simulations and experimental results.
  • It shows superiority over five other methods designed for incoherent sampling.
  • High accuracy is maintained even with significant bias in frequency estimation, particularly at high signal-to-noise ratios.

Conclusions:

  • The developed estimator effectively overcomes limitations imposed by incoherent sampling.
  • The modulation and DFT-based approach provides a robust solution for phase difference estimation.
  • This method offers a significant advancement for applications requiring precise phase difference measurements.