Department of Smart Air Mobility, Korea Aerospace University, Goyang-si 10540, Korea.
Department of Information and Communication Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, Korea.
Sensors (Basel). 2022 Apr 16;22(8):3073. doi: 10.3390/s22083073.
This paper proposes a high-speed continuous wavelet transform (CWT) processor to analyze vital signals extracted from a frequency-modulated continuous wave (FMCW) radar sensor. The proposed CWT processor consists of a fast Fourier transform (FFT) module, complex multiplier module, and inverse FFT (IFFT) module. For high-throughput processing, the FFT and IFFT modules are designed with the pipeline FFT architecture of radix-2 single-path delay feedback (R2SDF) and mixed-radix multipath delay commutator (MRMDC) architecture, respectively. In addition, the IFFT module and the complex multiplier module perform a four-channel operation to reduce the processing time from repeated operations. Simultaneously, the MRMDC IFFT module minimizes the circuit area by reducing the number of non-trivial multipliers by using a mixed-radix algorithm. In addition, the proposed CWT processor can support variable lengths of 8, 16, 32, 64, 128, 256, 512, and 1024 to analyze various vital signals. The proposed CWT processor was implemented in a field-programmable gate array (FPGA) device and verified through the measurement of heartbeat and respiration from an FMCW radar sensor. Experimental results showed that the proposed CWT processor can reduce the processing time by 48.4-fold and 40.7-fold compared to MATLAB software with Intel i7 CPU. Moreover, it can be confirmed that the proposed CWT processor can reduce the processing time by 73.3% compared to previous FPGA-based implementations.
本文提出了一种高速连续小波变换(CWT)处理器,用于分析从调频连续波(FMCW)雷达传感器中提取的生命信号。所提出的 CWT 处理器由快速傅里叶变换(FFT)模块、复数乘法器模块和逆快速傅里叶变换(IFFT)模块组成。为了实现高吞吐量处理,FFT 和 IFFT 模块分别采用基数-2 单路径延迟反馈(R2SDF)的流水线 FFT 架构和混合基数多路径延迟换向器(MRMDC)架构进行设计。此外,IFFT 模块和复数乘法器模块执行四路操作,通过重复操作减少处理时间。同时,MRMDC IFFT 模块通过使用混合基数算法减少非平凡乘法器的数量来最小化电路面积。此外,所提出的 CWT 处理器可以支持 8、16、32、64、128、256、512 和 1024 等可变长度,以分析各种生命信号。所提出的 CWT 处理器在现场可编程门阵列(FPGA)设备中实现,并通过 FMCW 雷达传感器测量心跳和呼吸进行验证。实验结果表明,与使用 Intel i7 CPU 的 MATLAB 软件相比,所提出的 CWT 处理器可以将处理时间减少 48.4 倍和 40.7 倍。此外,可以确认与以前基于 FPGA 的实现相比,所提出的 CWT 处理器可以将处理时间减少 73.3%。