An FPGA-Based YOLOv5n Accelerator for Online Multi-Track Particle Localization

Reliability testing for Single Event Effects (SEEs) requires accurate localization of heavy-ion tracks from projection images. Conventional localization often relies on handcrafted features and geometric fitting, which is sensitive to noise and difficult to accelerate in hardware. This paper presents a lightweight detector based on YOLOv5n that treats charge tracks in Topmetal pixel sensor projections as distinct objects and directly regresses the track angle and intercept, along with bounding boxes, in a single forward pass. On a synthetic dataset, the model achieves a precision of 0.9626 and a recall of 0.9493, with line-parameter errors of 0.3930° in angle and 0.4842 pixels in intercept. On experimental krypton beam data, the detector reaches a precision of 0.92 and a recall of 0.96, with a position resolution of 52.05 μm. We further deploy the model on an Xilinx Alveo U200, achieving an average per-frame accelerator latency of 3.1 ms while preserving measurement quality. This approach enables accurate, online track localization for SEE monitoring on Field-Programmable Gate Array (FPGA) platforms.