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OTFS Radar Waveform Design Based on Information Theory.

Qilong Miao1, Ling Kuang1, Ge Zhang1

  • 1School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.

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|February 26, 2025
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Summary
This summary is machine-generated.

This study optimizes radar waveforms using orthogonal time-frequency space (OTFS) by maximizing conditional mutual information (CMI). Optimized OTFS waveforms significantly improve target information extraction compared to random waveforms.

Keywords:
OTFSconditional mutual informationinformation theoryradarwaveform design

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Radar Systems

Background:

  • Orthogonal Time-Frequency Space (OTFS) modulation offers advantages for radar systems.
  • Assessing radar cognitive capability requires suitable performance metrics.
  • Waveform design is crucial for optimizing radar performance.

Purpose of the Study:

  • To design optimal OTFS waveforms for radar systems.
  • To utilize Conditional Mutual Information (CMI) as a criterion for waveform optimization.
  • To improve target information extraction capabilities of radar systems.

Main Methods:

  • Formulated the OTFS waveform design problem by maximizing CMI.
  • Proposed an equivalent waveform processing approach by minimizing autocorrelation sidelobes and cross-correlations (ASaCC) of the OTFS transmitting matrix.
  • Conducted simulations to compare optimized OTFS waveforms with random waveforms.

Main Results:

  • Optimized OTFS waveforms demonstrated superior performance in target information extraction.
  • Minimizing ASaCC of the OTFS transmitting matrix is an effective approach for waveform design.
  • The proposed method successfully enhances radar cognitive capabilities.

Conclusions:

  • The developed OTFS waveform design strategy based on CMI maximization and ASaCC minimization yields significant improvements in radar performance.
  • Optimized OTFS waveforms are highly effective for enhanced target information extraction.
  • This research contributes to the advancement of cognitive radar systems.