Temperature Self‐Adaptative Ultra‐Linear FMCW LiDAR Based on Chip‐Integrated Calibration Engine
Xianqi Pang, Baisong Chen, Xuetong Li, Yingzhi Li, Haolun Du, Ziming Wang, Heming Hu, Huan Qu, Zihao Zhi, Jie Li, Xiao‐Long Hu, Quanxin Na, Xueyan Li, Junfeng Song
Abstract
Abstract Frequency‐modulated continuous wave (FMCW) LiDAR offers high‐precision and long‐range sensing capabilities, making it well‐suited for industrial inspection and autonomous driving. However, in these applications, the environmental temperature is complex and variable, which imposes stringent requirements on the environmental robustness of the system. Maintaining linear frequency sweep in interfered environment becomes the key to determining system reliability. Conventional FMCW LiDAR systems mainly rely on offline pre‐distortion to correct laser nonlinearities, yet this approach is neither environmentally adaptive nor compatible with chip‐level integration owing to its dependence on discrete components. This study proposes an integrated detection and calibration engine, enabling a FMCW LiDAR system with real‐time closed‐loop adaptation to environmental temperature changes. The system achieves ultra‐low frequency sweep nonlinearity (1‐R 2 ) of 4.11 × 10 −8 , while demonstrating excellent environmental stability in temperature drift, 10‐hour high/low‐ temperature tests. Furthermore, it exhibits 480 µm ranging precision and meets automotive‐grade requirements with a detection range spanning 0.126 m to 202.7 m with 10% Lambertian reflectivity. To the best of the knowledge, this work demonstrates for the first time a temperature self‐adaptive FMCW LiDAR based on a chip‐integrated calibration engine, providing a reliable and real‐time calibration approach for next‐generation LiDAR systems.