Higher performance detectors are required for accurate, small form factor, low-cost, scalable LiDAR systems targeting long and short-range applications. SiPM and SPAD arrays are fast becoming the sensor of choice for both long and short-range LiDAR systems and are displacing legacy detectors such as linear avalanche photodiodes (APDs), owing to their high internal gain enabling single photon sensitivity and excellent uniformity across pixels. ON Semiconductor has a range of SiPM products with industry-leading sensitivity along with a unique Fast output mode which facilitates higher count rates. As the detector becomes more sensitive, the optical and signal chain requirements also change. A particular pain point for system designers, especially those used to working with legacy detectors, is how to start working with SiPMs and integrating them into their system. To ease this engineering design process, ON Semiconductor provides a wide range of evaluation kits which can help customers start making measurements quickly with SiPMs and reference designs which can be leveraged in part or in whole in a new LiDAR design. The kits range from simple readout boards for initial lab evaluation to facilitate learning to more advanced ready-to -use LiDAR reference designs. This presentation will detail the sensors used for direct time-of-flight LiDAR with a focus on the benefits of SiPM technology, along with the evaluation boards available. It will also cover the main types of LiDAR signal chains and the reference designs and kits available to date.
Bahman Hadji is Director of Business Development in the Automotive Sensing Division of onsemi’s Intelligent Sensing Group, where he’s responsible for bringing to market high-performance sensors used in LiDAR systems and enabling the LiDAR technology ecosystem to leverage the broad onsemi product portfolio. He has nearly 15 years of experience working with sensing devices, having worked for Aptina Imaging and OmniVision Technologies prior to joining onsemi in 2017. Bahman obtained both his Bachelor of Applied Science in Computer Engineering and Master of Applied Science in Electrical and Computer Engineering degrees from the University of Waterloo in Canada.