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Low-Complexity Joint Range and Doppler FMCW Radar Algorithm Based on Number of Targets.

Bong-Seok Kim1, Sangdong Kim1, Youngseok Jin1

  • 1Advanced Radar Technology Laboratory (ART Lab.), Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu 42988, Korea.

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|December 22, 2019
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Summary
This summary is machine-generated.

A new frequency-modulated continuous wave (FMCW) radar algorithm dynamically selects between two low-complexity methods based on the number of targets. This approach optimizes processing, reducing computational load for enhanced radar performance.

Keywords:
2D FFTFMCWlow complexitypartial DFT

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Radar Systems

Background:

  • Frequency-modulated continuous wave (FMCW) radar systems are crucial for various applications, including automotive and surveillance.
  • Existing low-complexity algorithms for FMCW radar, such as region of interest (ROI)-based and partial discrete Fourier transform (DFT)-based methods, have limitations in adaptability.
  • The computational complexity of FMCW radar algorithms is a significant factor affecting real-time performance.

Purpose of the Study:

  • To propose a novel, low-complexity joint range and Doppler FMCW radar algorithm.
  • To develop an adaptive algorithm that optimizes complexity based on the number of detected targets.
  • To demonstrate the effectiveness and efficiency of the proposed algorithm in real-world FMCW radar environments.

Main Methods:

  • Analysis of computational complexity for ROI-based and partial DFT-based FMCW radar algorithms.
  • Identification of the number of targets as a key determinant of algorithm complexity.
  • Development of a target-number-dependent algorithm that dynamically selects between two low-complexity FMCW radar processing strategies.

Main Results:

  • The number of targets significantly influences the complexity of FMCW radar algorithms.
  • The proposed adaptive algorithm achieves lower computational complexity compared to fixed low-complexity algorithms.
  • Experimental validation using real FMCW radar systems confirms the algorithm's effectiveness and efficiency, measured by CPU time and floating-point operations.

Conclusions:

  • The proposed FMCW radar algorithm effectively reduces computational complexity by adapting to the number of targets.
  • This adaptive approach offers a practical solution for enhancing the performance of real-time FMCW radar systems.
  • The algorithm demonstrates robust performance in practical scenarios, validated through real-world experiments.