Asynchronous timing between a SPAD detector and laser pulses, using deterministic or randomized offsets, reduces photon pileup and improves single-photon 3D depth accuracy by up to an order of magnitude in bright ambient light.
Photon-Flooded Single-Photon 3D Cameras
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abstract
Single photon avalanche diodes (SPADs) are starting to play a pivotal role in the development of photon-efficient, long-range LiDAR systems. However, due to non-linearities in their image formation model, a high photon flux (e.g., due to strong sunlight) leads to distortion of the incident temporal waveform, and potentially, large depth errors. Operating SPADs in low flux regimes can mitigate these distortions, but, often requires attenuating the signal and thus, results in low signal-to-noise ratio. In this paper, we address the following basic question: what is the optimal photon flux that a SPAD-based LiDAR should be operated in? We derive a closed form expression for the optimal flux, which is quasi-depth-invariant, and depends on the ambient light strength. The optimal flux is lower than what a SPAD typically measures in real world scenarios, but surprisingly, considerably higher than what is conventionally suggested for avoiding distortions. We propose a simple, adaptive approach for achieving the optimal flux by attenuating incident flux based on an estimate of ambient light strength. Using extensive simulations and a hardware prototype, we show that the optimal flux criterion holds for several depth estimators, under a wide range of illumination conditions.
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Asynchronous Single-Photon 3D Imaging
Asynchronous timing between a SPAD detector and laser pulses, using deterministic or randomized offsets, reduces photon pileup and improves single-photon 3D depth accuracy by up to an order of magnitude in bright ambient light.