Real-Time Proximity Sensing for Autonomous Systems: Custom AFE and FPGA Acceleration for FMCW Architecture

초록

In frequency-modulated continuous-wave (FMCW) light detection and ranging (LiDAR) systems, frequency modulation (FM) linearity and continuous-wave (CW) demodulation are the key factors determining overall performance. While most prior works focused on CPU-based linearization and decoding, this study presents a real-time FMCW architecture optimized for autonomous systems. While the system utilizes a generally robust distributed feedback (DFB) laser-based transmitter, it can be susceptible to temperature-induced frequency drift in dynamic autonomous environments. To address these fluctuations, an existing kernel-based nonlinearity tracking method was adopted and further extended into a coarse-to-fine framework for wide-range operation. The main design focus lies in the receiver, which includes a custom analog front-end (AFE) optimized for analog-to-digital converter (ADC) interfacing and multiply-accumulate (MAC) operations, along with a hardware-description-language (HDL)-based real-time decoding process. Experimental results in free space achieved a 0.15% error rate and 0.48-mm STD at 2 m, demonstrating the feasibility of the proposed architecture. In addition, an intensity measurement was conducted to verify the AFE performance.

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