An on-chip Pixel Processing Approach with 2.4μs latency for Asynchronous Read-out of SPAD-based dToF Flash LiDARs
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arXiv
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| Format: | Preprint |
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2025
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| author | Liu, Yiyang Zhang, Rongxuan Gyongy, Istvan Gorman, Alistair Patanwala, Sarrah M. Taneski, Filip Henderson, Robert K. |
| author_facet | Liu, Yiyang Zhang, Rongxuan Gyongy, Istvan Gorman, Alistair Patanwala, Sarrah M. Taneski, Filip Henderson, Robert K. |
| contents | 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$s latency for on-chip integration. Experiments demonstrate robust depth estimation, reflectivity reconstruction, and dynamic event-based representation under both static and dynamic conditions. The results confirm that asynchronous operation reduces redundant background data and computational load, while remaining tunable via simple hyperparameters. These findings establish a foundation for compact, low-latency, event-driven LiDAR architectures suited to robotics, autonomous driving, and consumer applications. In addition, we have derived a semi-closed-form solution for the detection probability of the raw-peak finding based LiDAR systems that could benefit both conventional frame-based and proposed asynchronous LiDAR systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_19192 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | An on-chip Pixel Processing Approach with 2.4μs latency for Asynchronous Read-out of SPAD-based dToF Flash LiDARs Liu, Yiyang Zhang, Rongxuan Gyongy, Istvan Gorman, Alistair Patanwala, Sarrah M. Taneski, Filip Henderson, Robert K. Image and Video Processing We propose a fully asynchronous peak detection approach for SPAD-based direct time-of-flight (dToF) flash LiDAR, enabling pixel-wise event-driven depth acquisition without global synchronization. By allowing pixels to independently report depth once a sufficient signal-to-noise ratio is achieved, the method reduces latency, mitigates motion blur, and increases effective frame rate compared to frame-based systems. The framework is validated under two hardware implementations: an offline 256$\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. |
| title | An on-chip Pixel Processing Approach with 2.4μs latency for Asynchronous Read-out of SPAD-based dToF Flash LiDARs |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2509.19192 |