• Title/Summary/Keyword: FMCW radarsensor

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Design of Radar Signal Processing System for Drone Detection (드론 검출을 위한 레이다 신호처리 시스템 설계)

  • Hong-suk Kim;Gyu-ri Ban;Ji-hun Seo;Yunho Jung
    • Journal of Advanced Navigation Technology
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    • v.28 no.5
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    • pp.601-609
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    • 2024
  • In this paper, we present the design and implementation results of a system that classifies drones from other objects using an FMCW (frequency-modulated continuous wave) radar sensor. The proposed system detects various objects through a four-stage signal processing procedure, consisting of FFT, CFAR, clustering, and tracking, using signals received from the radar sensor. Subsequently, a deep learning process is conducted to classify the detected objects as either drones or other objects. To mitigate the high computational demands and extensive memory requirements of deep learning, a BNN (binary neural network) structure was applied, binarizing the CNN (convolutional neural network) operations. The performance evaluation and verification results demonstrated a drone classification accuracy of 89.33%, with a total execution time of 4 ms, confirming the feasibility of real-time operation.