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FPGA Implementation of an Efficient FFT Processor for FMCW Radar Signal Processing.

Jinmoo Heo1, Yongchul Jung2, Seongjoo Lee3

  • 1Department of Smart Air Mobility, Korea Aerospace University, Goyang-si 10540, Korea.

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|October 13, 2021
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Summary

This study introduces an efficient hardware-based Fast Fourier Transform (FFT) processor for Frequency-Modulated Continuous Wave (FMCW) radar. The novel processor significantly accelerates signal processing, improving target detection rates and performance in vital sign measurements.

Keywords:
fast Fourier transform (FFT)field-programmable gate array (FPGA)frequency modulated continuous wave (FMCW) radarmemory-based FFT architecture

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Area of Science:

  • Electrical Engineering
  • Signal Processing
  • Radar Systems

Background:

  • Frequency-Modulated Continuous Wave (FMCW) radar systems require efficient signal processing for accurate target detection.
  • Traditional FMCW processing often relies on software for tasks beyond the Fast Fourier Transform (FFT), leading to performance bottlenecks.
  • Fixed-point operators in FFT processors can degrade performance, especially in demanding applications.

Purpose of the Study:

  • To design and implement an efficient hardware-based FFT processor tailored for FMCW radar signal processing.
  • To integrate essential signal processing functions, including windowing, accumulation, and magnitude/phase calculations, directly into the hardware.
  • To overcome the performance limitations of software-based processing and fixed-point arithmetic in FMCW radar systems.

Main Methods:

  • Development of a memory-based FFT architecture supporting variable lengths (64 to 4096).
  • Incorporation of a floating-point operator to maintain high precision and prevent performance degradation.
  • Hardware implementation of windowing, accumulation, and magnitude/phase calculation operations alongside the FFT.

Main Results:

  • The proposed FFT processor integrates multiple signal processing functions into hardware.
  • Achieved an execution time 7.32 times shorter compared to processors implementing only the FFT.
  • Utilized 1.69 times more hardware resources than a basic FFT-only processor, demonstrating a significant performance-resource trade-off.

Conclusions:

  • The developed hardware FFT processor offers substantial acceleration for FMCW radar signal processing.
  • Integrated hardware functions enable faster and potentially more accurate target detection and vital sign measurement.
  • The design provides an efficient solution for real-time FMCW radar applications demanding high computational throughput.