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Information-Theoretic Radar Waveform Design under the SINR Constraint.

Yu Xiao1,2, Zhenghong Deng1, Tao Wu3

  • 1School of Automation, Northwestern Polytechnical University, Xi'an 710072, China.

Entropy (Basel, Switzerland)
|December 8, 2020
PubMed
Summary
This summary is machine-generated.

This study optimizes radar waveform design using information theory for better performance in clutter. New methods maximize mutual information for estimation and Kullback-Leibler divergence for detection, improving target identification.

Keywords:
SINR constraintenergy allocation strategiesfrequency domaininformation–theoreticwaveform optimization

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Area of Science:

  • Radar Systems Engineering
  • Information Theory
  • Signal Processing

Background:

  • Radar systems face challenges in signal-dependent clutter environments, impacting performance.
  • Optimizing waveform design is crucial for enhancing radar capabilities in complex scenarios.

Purpose of the Study:

  • To investigate information-theoretic criteria for radar waveform design.
  • To establish trade-offs between information theory and signal-to-interference-plus-noise ratio (SINR) for optimal energy allocation.
  • To develop waveform design strategies for improved radar estimation and detection.

Main Methods:

  • Developed a frequency-domain model for mutual information (MI), Kullback-Leibler divergence (KLD), and SINR constraints.
  • Derived the effects of SINR on maximizing MI and KLD under energy constraints.
  • Proposed optimal radar waveform methods based on maximizing MI for estimation and KLD for detection.

Main Results:

  • Established bounds for maximum MI (by SINR) and KLD (0 to Jenson-Shannon divergence).
  • MI-based waveforms effectively allocate energy for target information extraction in clutter.
  • KLD-based waveforms efficiently allocate energy for target detection by maximizing target spectrum presence.

Conclusions:

  • Information-theoretic approaches provide effective strategies for radar waveform design in signal-dependent clutter.
  • The proposed MI and KLD maximization methods offer distinct advantages for radar estimation and detection, respectively.
  • Optimized energy allocation in the frequency domain significantly enhances radar performance and target discernment.