Real-Time Correlation Processing of Vibroacoustic Signals on Single Board Raspberry Pi Computers with HiFiBerry Cards

The paper discusses the implementation of a time-frequency correlation algorithm for time delay estimation (TDE) on Raspberry Pi single-board computers. The implemented correlation algorithm is based on Fourier transform with the frequency sweep. In the paper, we analyzed the task of real-time acquisition and processing of acoustic signals with the Raspberry Pi computers. Then we modified the algorithm of computation of time frequency-correlation function to be applicable in real-time and implemented it as a C++ object. To increase the performance, we implemented GPU acceleration using GPU_FFT and Vulkan FFT libraries. The first library is a firmware that utilizes VideoCore IV on Raspberry Pi 3B+. Vulkan FFT library was implemented as an alternative compatible with VideoCore VI on Raspberry 4B. To estimate the efficiency of applying the graphical cores to we conducted a set of experiments. Those experiments were designed to measure the reduction in processing time after accelerating the most time computationally operation of inverse Fourier transform with theGPU. According to the results, we have concluded that GPU acceleration is efficient and makes possible the real-time processing of acoustic signals even of Raspberry Pi 3B+. The GPU acceleration proved to be the most crucial when large Fourier transform window size and the significant number of frequency bands are used.