Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA.
Biosensors (Basel). 2022 Apr 12;12(4):236. doi: 10.3390/bios12040236.
Correlation has a variety of applications that require signal processing. However, it is computationally intensive, and software correlators require high-performance processors for real-time data analysis. This is a challenge for embedded devices because of the limitation of computing resources. Hardware correlators that use Field Programmable Gate Array (FPGA) technology can significantly boost computational power and bridge the gap between the need for high-performance computing and the limited processing power available in embedded devices. This paper presents a detailed FPGA-based correlator design at the register level along with the open-source Very High-Speed Integrated Circuit Hardware Description Language (VHDL) code. It includes base modules for linear and multi-tau correlators of varying sizes. Every module implements a simple and unified data interface for easy integration with standard and publicly available FPGA modules. Eighty-lag linear and multi-tau correlators were built for validation of the design. Three input data sets-constant signal, pulse signal, and sine signal-were used to test the accuracy of the correlators. The results from the FPGA correlators were compared against the outputs of equivalent software correlators and validated with the corresponding theoretical values. The FPGA correlators returned results identical to those from the software references for all tested data sets and were proven to be equivalent to their software counterparts. Their computation speed is at least 85,000 times faster than the software correlators running on a Xilinx MicroBlaze processor. The FPGA correlator can be easily implemented, especially on System on a Chip (SoC) integrated circuits that have processor cores and FPGA fabric. It is the ideal component for device-on-chip solutions in biosensing.
相关技术在需要信号处理的各种应用中都有广泛的应用。然而,它的计算量很大,软件相关器需要高性能的处理器来进行实时数据分析。对于嵌入式设备来说,这是一个挑战,因为它们的计算资源有限。使用现场可编程门阵列 (FPGA) 技术的硬件相关器可以显著提高计算能力,并弥合高性能计算的需求与嵌入式设备可用处理能力之间的差距。本文提出了一种详细的基于 FPGA 的相关器设计,包括寄存器级别的设计和开源的超高速集成电路硬件描述语言 (VHDL) 代码。它包括用于不同大小的线性和多延迟相关器的基本模块。每个模块都实现了简单且统一的数据接口,便于与标准和公开可用的 FPGA 模块集成。构建了 80 个延迟的线性和多延迟相关器来验证设计。使用三个输入数据集——恒信号、脉冲信号和正弦信号——来测试相关器的准确性。将 FPGA 相关器的结果与等效软件相关器的输出进行比较,并与相应的理论值进行验证。对于所有测试数据集,FPGA 相关器的结果都与软件参考结果一致,证明它们与软件对应物等效。它们的计算速度至少比在 Xilinx MicroBlaze 处理器上运行的软件相关器快 85000 倍。FPGA 相关器易于实现,尤其是在具有处理器内核和 FPGA 结构的片上系统 (SoC) 集成电路上。它是生物传感设备芯片解决方案的理想组件。