First Arrival Differential LiDAR

Tianyi Zhang, Mel White, Akshat Dave, Shahaboddin Ghajari, Ankit Raghuram, Alyosha Molnar, Ashok Veeraraghavan

Abstract: Single-photon avalanche diode (SPAD) based LiDAR is becoming the de-facto choice for 3D imaging in many emerging applications. However, they suffer from three significant limitations: (a) the additional time-of-arrival dimension results in a data throughput bottleneck, (b) limited spatial resolution due to either low fill-factor (flash LiDAR) or scanning time (scanning-based LiDAR), and (c) coarse depth resolution due to quantization of photon timing by existing SPAD timing circuitries. In this paper, we present a novel, in-pixel computing architecture that we term first arrival differential (FAD) LiDAR, where instead of recording quantized time-of-arrival information at individual pixels, we record a temporal differential measurement between pairs of pixels. FAD captures relative order of photon arrivals at the two pixels (within a cycle or laser period) and creates a one-to-one mapping between this differential measurement and depth differences between the two pixels. We perform detailed system analysis and characterization using Monte Carlo simulation, and experimental emulation using a scanning-based single-photon avalanche diode. FAD pixels can result in a 10–100x reduction in per-pixel data throughput compared to TDC-based pixels. Under the same bandwidth constraints, FAD-LiDAR achieves better depth resolution and/or range than several state-of-the-art TDC-based LiDAR baselines.