Breaking the temporal and frequency congestion of LiDAR by parallel chaos

The rising demand for high scanning accuracy and resolution in sensors for self-driving vehicles has led to the rapid development of parallelization in light detection and ranging (LiDAR) technologies. However, for the two major existing LiDAR categories-time-of-flight and frequency-modulated continuous wave-the light sources and measurement principles currently used for parallel detection face severe limitations from time- and frequency-domain congestion, leading to degraded measurement performance and increased system complexity. In this work we introduce a light source-the chaotic microcomb-to overcome this problem. This physical entropy light source exhibits naturally orthogonalized light channels that are immune to any congestion problem. Based on this microcomb state, we demonstrate a new type of LiDAR-parallel chaotic LiDAR-that is interference-free and has a greatly simplified system architecture. Our approach also enables the state-of-the-art ranging performance among parallel LiDARs: millimetre-level ranging accuracy and millimetre-per-second-level velocity resolution. Combining all of these desirable properties, this technology has the potential to reshape the entire LiDAR ecosystem. Current LiDAR approaches suffer from congestion issues, which affect measurement performance and increased system complexity. Now researchers demonstrate a chaotic microcomb that exhibits congestion-immune naturally orthogonalized light channels.