基于SPAD的闪光激光雷达实现2.4微秒级异步像素处理，显著降低延迟并提升动态场景感知能力。
An on-chip Pixel Processing Approach with 2.4μs latency for Asynchronous Read-out of SPAD-based dToF Flash LiDARs
- 像素独立触发深度检测，无需全局同步，实现事件驱动式测距。
- 实测在FPGA上达成2.4μs芯片内延迟，有效帧率显著提升。
- 适用于机器人、自动驾驶等对低延迟敏感的应用场景。
本文提出一种全异步的峰值检测方法，用于基于单光子雪崩二极管（SPAD）的直接飞行时间（dToF）闪光激光雷达，实现像素级事件驱动的深度获取，无需全局同步。各像素在信号噪声比达到阈值后独立报告深度，降低了延迟，减轻了运动模糊，并提升了有效帧率。该框架通过两种硬件实现验证：一种是基于PC处理的256×128 SPAD阵列离线系统，另一种是实时FPGA原型系统，后者实现了2.4μs的芯片内延迟。实验表明，在静态与动态条件下均能实现鲁棒的深度估计、反射率重建及动态事件表示。结果证明，异步操作可减少冗余背景数据和计算负载，且可通过简单超参数调节。研究为紧凑、低延迟、事件驱动的激光雷达架构奠定了基础，适用于机器人、自动驾驶和消费类应用。此外，我们推导出基于原始峰值检测的激光雷达系统检测概率的半闭式解，可同时惠及传统帧基与提出的异步系统。
原文摘要 · Abstract (English)
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.
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