UC Berkeley

LiDAR (Light Detection and Ranging) captures high-definition real-time 3D images of the surrounding environment through active sensing with infrared lasers. It has unique advantages that can compensate the fundamental limitations in camera-based 3D imaging via vision algorithms or RADARs, which makes it an important sensing modality to guarantee robust autonomy in self-driving cars. However, high price tag of existing commercial LiDAR modules based on mechanical beam scanners and intensity-based detection scheme makes them unusable in the context of mass produced consumer products.

The focus of thesis is on the integrated coherent LiDAR with optical phased array-based solid-state beam steering, which has great potential to dramatically bring down the cost of a LiDAR module. It begins with an overview of LiDAR implementation options and system requirements in the context of autonomous vehicles, which leads us to conclude that beam-steering coherent FMCW LiDAR in optical C-band is indeed the best implementation strategy to realize low-cost automotive LiDARs. Motivated by this observation, a quantitative framework for evaluating FMCW LiDAR performance is also introduced to predict the design that satisfies car-grade performance requirements. Then the thesis presents the silicon implementation results from our single-chip optical phased array and integrated coherent LiDAR prototype. Our implementations leverage the 3D heterogeneous integration platform, where custom silicon photonics and nanoscale CMOS fabricated at a 300 mm wafer facility are combined at the wafer-scale to minimize the unit cost without I/O density issues. After discussing remaining challenges and possible ways to enhance the operating range and system reliability, this thesis finally addresses the problem of fundamental trade-off between phase noise and wavelength tuning in FMCW laser source, and present circuit- and algorithm-level techniques to enable FMCW measurements beyond inherent laser coherence range limit.