Photonic-crystal lasers with high-quality narrow-divergence symmetric beams and their application to LiDAR

Light detection and ranging (LiDAR) is a key technology for smart mobility of robots, agricultural and construction machines, and autonomous vehicles. However, current LiDAR systems often rely on semiconductor lasers with low-quality, large-divergence, and asymmetric beams, requiring high-precision integration of complicated lens systems to reshape the beam. Also, due to the broad linewidth and the large temperature dependence of their lasing spectrum, a bandpass filter with broad bandwidth must be used in front of the detector, so the detected signal is affected by noise from background light such as sunlight. These critical issues limit the performance, compactness, affordability, and reliability of the LiDAR systems. Photonic-crystal surface-emitting lasers (PCSELs) have attracted much attention as novel semiconductor lasers that can solve the issues of conventional semiconductor lasers owing to their capability of high-quality, very-narrow-divergence, and symmetric beam operation supported by broad-area band-edge resonance in their two-dimensional photonic crystal. In this paper, we show the progress and the state of the art of broad-area coherent PCSELs and their application to a time-of-flight (ToF) LiDAR system. We first review the progress of PCSELs made so far. Next, we show recent progress based on PCSELs with a double-lattice structure that enables higher-power and narrower-divergence operation while keeping a symmetric beam shape. By optimizing the double-lattice photonic crystal and the reflective properties of a backside distributed Bragg reflector (DBR), we achieve a high peak power of 10 W while maintaining a nearly diffraction-limited beam divergence of ∼0.1° (FWHM) from a 500 µ m diameter resonator. Using this PCSEL, we construct a LiDAR system that uses no external lens system in its light source and demonstrate highly spatially resolved ToF sensing (measurement range of ∼20 m), which is appropriate for autonomous robots and factory automation.