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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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Updated: Dec 21, 2025

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A Novel High-Frequency Vibration Error Estimation and Compensation Algorithm for THz-SAR Imaging Based on Local FrFT.

Yinwei Li1,2,3, Li Ding1,2, Qibin Zheng1,2

  • 1Terahertz Technology Innovation Research Institute, University of Shanghai for Science and Technology, Shanghai 200093, China.

Sensors (Basel, Switzerland)
|May 13, 2020
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Summary

This study introduces a new algorithm to reduce image quality issues in terahertz synthetic aperture radar (THz-SAR) caused by platform vibrations. The method effectively estimates and compensates for high-frequency vibration errors, improving THz-SAR imaging.

Keywords:
high-frequency vibration errorlocal fractional Fourier transform (LFrFT)sinusoidal frequency modulation (SFM)terahertz synthetic aperture radar (THz-SAR) imaging

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Area of Science:

  • Remote Sensing
  • Electromagnetics
  • Signal Processing

Background:

  • Terahertz synthetic aperture radar (THz-SAR) offers ultrahigh-resolution imaging potential due to its high frequency and short wavelength.
  • Image quality in THz-SAR is highly susceptible to high-frequency vibrations from the motion platform.
  • Existing methods may struggle to accurately address these vibration-induced errors.

Purpose of the Study:

  • To propose a novel algorithm for estimating and compensating high-frequency vibration errors in THz-SAR imaging.
  • To enhance the image quality and reliability of THz-SAR systems operating under dynamic conditions.
  • To provide a robust solution for mitigating motion platform disturbances in high-resolution THz-SAR.

Main Methods:

  • Modeling high-frequency vibration error as simple harmonic motion and THz-SAR echo signals as sinusoidal frequency modulation (SFM) signals.
  • Developing a parameter estimation algorithm for SFM signals utilizing the local fractional Fourier transform (LFrFT).
  • Estimating vibration acceleration and frequency using LFrFT and spectrum analysis, followed by SFM signal reconstruction and phase error compensation.

Main Results:

  • Successfully estimated vibration acceleration and frequency of the motion platform.
  • Reconstructed the SFM signal with high accuracy.
  • Demonstrated effective compensation of phase errors caused by high-frequency vibrations through simulations.
  • Validated the proposed algorithm's effectiveness in improving THz-SAR imaging.

Conclusions:

  • The proposed LFrFT-based algorithm provides an effective method for high-frequency vibration error estimation and compensation in THz-SAR.
  • This technique significantly improves THz-SAR image quality by mitigating motion platform disturbances.
  • The findings contribute to the advancement of high-resolution THz-SAR imaging applications.