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[The study of maximum entropy method used in wind profiler].

Ming-bao Hu1, Guo-guang Zheng, Pei-chang Zhang

  • 1Nanjing University of Information Science & Technology, Nanjing 210044, China. humb2005@sina.com

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|June 22, 2012
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Summary

The maximum entropy method (MEM) outperforms fast Fourier transform (FFT) for weak wind profiler radar echoes, effectively reducing ground clutter and white noise. Optimal results are achieved with approximately 15 iterative steps.

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Area of Science:

  • Atmospheric Science
  • Signal Processing
  • Radar Meteorology

Context:

  • Wind profiler radars are crucial for atmospheric monitoring.
  • Traditional spectrum analysis methods like Fast Fourier Transform (FFT) face challenges with weak signals and interference.
  • Evaluating advanced techniques is essential for improving data quality.

Purpose:

  • To compare the effectiveness of the Maximum Entropy Method (MEM) against the Fast Fourier Transform (FFT) for spectrum analysis in wind profiler radar.
  • To assess the performance of MEM in handling weak radar echoes, ground clutter, and white noise.
  • To determine the optimal number of iterative steps for MEM in this application.

Summary:

  • Both MEM and FFT perform comparably with strong radar echoes.
  • MEM demonstrates superior performance with weak echoes, effectively mitigating ground clutter contamination.
  • MEM-derived spectra are smoother, aiding in the reduction of white noise influence.
  • The number of iterative steps in MEM impacts spectral results, with approximately 15 steps yielding optimal outcomes, as guided by the Final Prediction Error (FPE) rule.

Impact:

  • The findings provide practical guidance for enhancing spectrum analysis in wind profiler radar systems.
  • Improved spectrum analysis can lead to more accurate wind speed and direction measurements.
  • This research contributes to the advancement of atmospheric remote sensing technologies.