{"ID":2867254,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.19192","arxiv_id":"2509.19192","title":"An on-chip Pixel Processing Approach with 2.4μs latency for Asynchronous Read-out of SPAD-based dToF Flash LiDARs","abstract":"We propose a fully asynchronous peak detection approach for SPAD-based direct time-of-flight (dToF) flash LiDAR, enabling pixel-wise event-driven depth acquisition without global synchronization. By allowing pixels to independently report depth once a sufficient signal-to-noise ratio is achieved, the method reduces latency, mitigates motion blur, and increases effective frame rate compared to frame-based systems. The framework is validated under two hardware implementations: an offline 256$\\times$128 SPAD array with PC based processing and a real-time FPGA proof-of-concept prototype with 2.4$\\upmu$s latency for on-chip integration. Experiments demonstrate robust depth estimation, reflectivity reconstruction, and dynamic event-based representation under both static and dynamic conditions. The results confirm that asynchronous operation reduces redundant background data and computational load, while remaining tunable via simple hyperparameters. These findings establish a foundation for compact, low-latency, event-driven LiDAR architectures suited to robotics, autonomous driving, and consumer applications. In addition, we have derived a semi-closed-form solution for the detection probability of the raw-peak finding based LiDAR systems that could benefit both conventional frame-based and proposed asynchronous LiDAR systems.","short_abstract":"We propose a fully asynchronous peak detection approach for SPAD-based direct time-of-flight (dToF) flash LiDAR, enabling pixel-wise event-driven depth acquisition without global synchronization. By allowing pixels to independently report depth once a sufficient signal-to-noise ratio is achieved, the method reduces lat...","url_abs":"https://arxiv.org/abs/2509.19192","url_pdf":"https://arxiv.org/pdf/2509.19192v3","authors":"[\"Yiyang Liu\",\"Rongxuan Zhang\",\"Istvan Gyongy\",\"Alistair Gorman\",\"Sarrah M. Patanwala\",\"Filip Taneski\",\"Robert K. Henderson\"]","published":"2025-09-23T16:11:30Z","proceeding":"eess.IV","tasks":"[\"eess.IV\"]","methods":"[]","has_code":false}