Enhanced FFT–Root–MUSIC Algorithm Based on Signal Reconstruction via CEEMD–SVD for Joint Range and Velocity Estimation for FMCW Radar
2024

Enhanced FFT–Root–MUSIC Algorithm for FMCW Radar

publication 10 minutes Evidence: high

Author Information

Author(s): Cao Jiaxin, Yi Huiyue, Zhang Wuxiong, Xu Hui, Sun Guangcai

Primary Institution: Key Laboratory of Science and Technology on Micro-System, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences

Hypothesis

The proposed CEEMD-SVD-FRM algorithm will improve joint range and velocity estimation for FMCW radar in low SNR conditions.

Conclusion

The CEEMD-SVD-FRM algorithm significantly enhances the accuracy and robustness of joint range and velocity estimation for FMCW radar, especially in low SNR environments.

Supporting Evidence

  • The CEEMD-SVD-FRM algorithm was validated through simulations and experiments.
  • It demonstrated significant improvement in the robustness and accuracy of range and velocity estimates for FMCW radar.
  • The proposed method outperformed traditional algorithms in low SNR environments.

Takeaway

This study created a new way to help radar measure how far away things are and how fast they're moving, even when the signals are really noisy.

Methodology

The study used CEEMD and SVD to denoise the radar signals before applying the FFT-Root-MUSIC algorithm for estimating range and velocity.

Limitations

The computational complexity of the CEEMD-SVD-FRM algorithm is higher than some traditional methods, which may limit its practical application in real-time systems.

Digital Object Identifier (DOI)

10.3390/s24248000

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