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A Convolutional Neural Network-Based Method for Discriminating Shadowed Targets in Frequency-Modulated

Ammar Mohanna1, Christian Gianoglio1, Ali Rizik1

  • 1Department of Electrical, Electronic and Telecommunication Engineering and Naval Architecture (DITEN), University of Genoa, Via Opera Pia 11, 16145 Genoa, Italy.

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Summary
This summary is machine-generated.

This study introduces a new Convolutional Neural Network method to overcome the radar shadow effect in Frequency-Modulated Continuous-Wave (FMCW) radars. The approach accurately identifies targets obscured by other objects, improving radar performance.

Keywords:
CNNmachine learningradarshadow effecttransfer learning

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Area of Science:

  • * Radar Systems Engineering
  • * Machine Learning Applications
  • * Signal Processing

Background:

  • * The radar shadow effect hinders accurate target detection when one object obstructs another.
  • * Frequency-Modulated Continuous-Wave (FMCW) radars are increasingly used due to their cost-effectiveness and compact size.
  • * Reliable target discrimination is crucial for various applications, including automotive and surveillance.

Purpose of the Study:

  • * To develop a novel method for overcoming the radar shadow effect in FMCW radar systems.
  • * To enhance the capability of FMCW radars in discerning targets within the shadow region of other objects.
  • * To improve the reliability of target discrimination in complex radar environments.

Main Methods:

  • * Utilized Short-Time Fourier Transform (STFT) analysis to process radar-received signals.
  • * Developed a Convolutional Neural Network (CNN) model that analyzes spectrograms.
  • * Trained the CNN to differentiate between targets in shadow regions and those clearly visible.

Main Results:

  • * The proposed CNN-based method achieved a test accuracy of 92%.
  • * The method demonstrated a low standard deviation of 2.86%, indicating consistent performance.
  • * Successfully discerned whether targets were located within the shadow region of other objects.

Conclusions:

  • * The novel CNN approach effectively addresses the radar shadow effect in FMCW systems.
  • * The method offers a significant improvement in target discrimination accuracy.
  • * This technique enhances the practical utility of low-cost FMCW radars in challenging scenarios.