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Micro-Doppler Signal Time-Frequency Algorithm Based on STFRFT.

Cunsuo Pang1, Yan Han2, Huiling Hou3

  • 1National Key Laboratory for Electronic Measurement Technology, North University of China, Taiyuan 030051, China. pangcunsuo@126.com.

Sensors (Basel, Switzerland)
|September 27, 2016
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Summary
This summary is machine-generated.

This study introduces a new time-frequency algorithm using short-time fractional order Fourier transformation (STFRFT) for complex target identification. The method enhances accuracy and reduces computation for micro-Doppler analysis in radar systems.

Keywords:
Micro Doppler frequencymulti-order matchingorder selectionshort-time fractional order Fourier transformation

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Area of Science:

  • Signal Processing
  • Radar Systems Engineering
  • Target Identification

Background:

  • Accurate identification of complex moving targets is crucial for radar applications.
  • Existing time-frequency analysis methods face challenges with computational load and accuracy for intricate signals.
  • Micro-Doppler signatures offer valuable information for distinguishing targets.

Purpose of the Study:

  • To propose a novel time-frequency algorithm for complex target identification.
  • To enhance the accuracy and efficiency of micro-Doppler analysis.
  • To reduce the computational complexity associated with target recognition algorithms.

Main Methods:

  • Development of a time-frequency algorithm based on short-time fractional order Fourier transformation (STFRFT).
  • Implementation of an STFRFT order-changing and quick selection method to reduce computation.
  • Design of a multi-order STFRFT algorithm leveraging time-frequency features of micro-Doppler components.
  • Utilizing multi-order matching for improved time-frequency curve fitting estimation accuracy.

Main Results:

  • Experimental validation of the STFRFT algorithm's performance in micro-Doppler time-frequency analysis.
  • Demonstrated higher estimation accuracy compared to existing methods.
  • The proposed algorithm effectively reduces computational load.
  • Successful application to simulated LFM, SAR, and ISAR data.

Conclusions:

  • The proposed STFRFT-based time-frequency algorithm significantly improves estimation accuracy for complex target identification.
  • The algorithm offers a computationally efficient approach for micro-Doppler analysis.
  • Potential applications include LFM, SAR, and ISAR radar systems to enhance target recognition probability.