Coded Pulse Stream LiDAR Based on Optical Orthogonal Frequency-Division Multiple Access

In future mobility, robust obstacle detection is imperative for autonomous vehicles, fostering a reliance on vision-based data and the emergence of light detection and ranging (LiDAR) as a pivotal sensor. Despite challenges of cost and novelty, LiDAR’s unique capabilities find favor among automakers, except Tesla. Offering 3D imaging with superior resolution than radar, LiDAR holds potential significance as a perception sensor for safe and efficient transportation. Its 3D distance measurement using laser pulses and waveform analysis is vital for obstacle detection in autonomous vehicles. Techniques like scanning and flash LiDAR optimize point cloud acquisition, albeit with challenges in balancing resolution and frame rates. Because LiDAR measures the distance to an object using the time-of-flight, the idle listening time required to detect reflected waves increases in proportion to the maximum distance. Both, lateral angular resolution and frame rates are dependent on this idle listening time. Lateral angular resolution impacts LiDAR’s ability to detect objects. This study proposes an optical orthogonal frequency-division multiple access (OFDMA) LiDAR with a coded pulse technique to enhance the detection accuracy of objects. Simulation results demonstrate that the proposed OFDMA LiDAR overcoming false positives and mutual interference through pulse stream LiDARs and strategic approaches is crucial in LiDAR’s integration into future mobility systems.