Direct time-of-flight (dToF) sensors that measure depth by pulsing a laser and timing the photon return are used in many applications, including consumer electronics for proximity sensing and depth map generation. A histogram of photon return times is measured and then processed to estimate object depth. By collecting many photons that span multiple bins of the histogram the final depth estimate interpolates between time-to-digital converter (TDC) bins to produce a result that is more precise than the converter resolution. The precision of this interpolation depends on the temporal spread of the measurement, the resolution of the TDC, and the number of signal and background photons measured. There is a need for dToF depth precision models to guide design and predict and tune performance during use. In this article, we present models that estimate sensor depth precision versus dToF design parameters and photons measured. We use Monte Carlo simulations and experimental measurements to prove the accuracy of the models. With proven models in hand, we investigate a dToF sensor design by first presenting the dependence of precision upon the TDC resolution and the signal-to-noise ratio. Second, we experimentally measure the depth precision versus the intensity of background illumination. The models closely match the measurements of background susceptibility and locate a transition point of background intensity below which precision is constant and above which the precision continuously degrades. Finally, experimental measurements demonstrate how the modeling enables dynamic tuning: from a single histogram we estimate precision, thus enabling sensor exposure time tuning for a target precision or prediction of the precision given a change in object distance or background illumination. This work presents straightforward models verified by simulation and measurement. These models guide dToF design and enable dynamic adjustments that benefit power-constrained usage scenarios.

中文翻译：

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可实现最佳设计和动态配置的直接飞行时间传感器精度模型

直接飞行时间（dToF）传感器通过脉冲激光来测量深度并定时返回光子，已用于许多应用中，包括用于接近感应和深度图生成的消费类电子产品。测量光子返回时间的直方图，然后进行处理以估计物体深度。通过收集跨越直方图多个bin的许多光子，最终的深度估计值将在时间数字转换器（TDC）bin之间进行插值，以产生比转换器分辨率更精确的结果。此插值的精度取决于测量的时间范围，TDC的分辨率以及所测量的信号和背景光子的数量。需要使用dToF深度精度模型来指导设计以及使用期间的预测和性能调整。在本文中，我们提供的模型可估算传感器深度精度与dToF设计参数和测得的光子之间的关系。我们使用蒙特卡洛模拟和实验测量来证明模型的准确性。借助经过验证的模型，我们首先研究精度对TDC分辨率和信噪比的依赖性，从而研究dToF传感器的设计。其次，我们通过实验测量深度精度与背景照明强度之间的关系。这些模型与背景磁化率的测量值紧密匹配，并找到背景强度的过渡点，在该过渡点以下，精度是恒定的，而在其之上，精度会不断下降。最后，实验测量结果证明了建模如何实现动态调整：根据单个直方图，我们估算精度，因此，可以根据目标距离或背景照明的变化，调整传感器曝光时间，以达到目标精度或预测精度。这项工作提出了通过仿真和测量验证的简单模型。这些模型指导dToF设计并实现动态调整，从而有利于功耗受限的使用场景。