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Related Experiment Video

Updated: Jun 3, 2025

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Enhanced FFT-Root-MUSIC Algorithm Based on Signal Reconstruction via CEEMD-SVD for Joint Range and Velocity

Jiaxin Cao1,2, Huiyue Yi1, Wuxiong Zhang1

  • 1Key Laboratory of Science and Technology on Micro-System, Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences, Shanghai 200050, China.

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|January 8, 2025
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Summary

This study introduces a new method for Frequency-Modulated Continuous-Wave (FMCW) radar to improve range and velocity estimation. The CEEMD-SVD-FRM algorithm enhances accuracy in noisy, low signal-to-noise ratio (SNR) environments.

Keywords:
CEEMDFFT-Root-MUSIC algorithmFMCW radarSVDjoint range–velocity estimation

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Area of Science:

  • Radar Systems Engineering
  • Signal Processing
  • Data Analysis

Background:

  • Traditional joint range-velocity estimation in FMCW radar suffers performance degradation in low signal-to-noise ratio (SNR) conditions.
  • Additive white Gaussian noise significantly impacts the accuracy of beat signal analysis.

Purpose of the Study:

  • To propose a novel algorithm for robust joint range-velocity estimation in FMCW radar, particularly effective in low SNR environments.
  • To enhance the accuracy and reliability of target parameter extraction by improving the signal-to-noise ratio of the beat signal.

Main Methods:

  • Utilizing Complementary Ensemble Empirical Mode Decomposition (CEEMD) to decompose the noisy beat signal.
  • Applying Singular Value Decomposition (SVD) to selected intrinsic mode functions (IMFs) for effective signal denoising.
  • Reconstructing the denoised beat signal by combining IMFs and residuals.
  • Employing the FFT-Root-MUSIC algorithm on the reconstructed signal for joint range and velocity estimation.

Main Results:

  • The proposed CEEMD-SVD-FRM algorithm demonstrates significant improvements in the robustness and accuracy of range and velocity estimates.
  • Effective denoising of the beat signal leads to superior performance compared to traditional methods, especially in low SNR conditions.
  • Simulations and experimental validation confirm the algorithm's effectiveness.

Conclusions:

  • The CEEMD-SVD-FRM algorithm offers a substantial advancement for FMCW radar systems requiring precise range and velocity measurements.
  • The combined CEEMD and SVD approach provides effective noise reduction, enabling reliable target detection and parameter estimation even with weak signals.
  • This method significantly enhances FMCW radar capabilities in challenging, low SNR operational scenarios.