Solid-State dToF LiDAR System Using an Eight-Channel Addressable, 20-W/Ch Transmitter, and a 128 × 128 SPAD Receiver With SNR-Based Pixel Binning and Resolution Upscaling

Abstract

An entire solid-state direct time-of-flight (dToF) light detection and ranging (LiDAR) system that incorporates innovations for both the transmitter (TX) and the receiver (RX) is presented in this work. For the illumination TX, we demonstrate solid-state channel addressability, which significantly reduces the transmit power and improves the ranging distance by dividing the field of view (FoV) into separately illuminated sub-regions. In the RX, we introduce single-photon avalanche diodes (SPADs) pixel binning, which enables reconfigurability of the sensor’s spatial resolution. Finally, we introduce a machine learning (ML) technique that enables this pixel-binned depth sensor to upscale its spatial resolution after training/inference fusion with the intensity image. The laser diode driver (LDD) chip is implemented in the 180-nm bipolar-CMOS-DMOS (BCD) process and is capable of pumping more than 8-A peak current into a multi-junction vertical-cavity surface-emitting laser (VCSEL) array, producing up to 20.3-W optical pulses under 12.5-V supply voltage. The sensor chip is also implemented in the 180-nm BCD process with a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$128 \times 128$ </tex-math></inline-formula> SPAD array and reconfigurable pixel binning. Hardware and software co-optimization under low signal-to-noise ratio (SNR) conditions with ML-based spatial resolution upscaling is demonstrated.