Low-complexity Depth-sensing Algorithm and Architecture Design for Chaotic LiDAR System

• Main Authors: Guo, Jia-Jun, 郭家均
• Other Authors: Huang, Yuan-Hao
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/975h6p

碩士 === 國立清華大學 === 電機工程學系 === 107 === LiDAR, Light Detection and Ranging, is a remote-sensing technique applied generally to geodesy, atmospheric physics and even autonomous cars. The approach for depth- sensing of LiDAR systems is illuminating the target with laser signal and deriving the time difference, named time of flight (TOF), between the reflected signal (target signal) and the transmitted one (reference signal). Among numerical kinds of LiDAR systems, the chaotic LiDAR (CLiDAR) system is used most commonly for its noise-like wave- form beams which enable us to find the time of flight simply by correlating the target signal with the reference one. Nevertheless, the amount of computation increases with the extension of the detectable range and the length of the signal. The phenomenon is a concerned issue of CLiDAR. Therefore, the study proposed a low-complexity al- gorithm for depth sensing of CLiDAR. The proposed algorithm reduces the amount of computation to 15% of the traditional one with tiny loss of performance. The hardware of the time-of-flight calculation unit is implemented in this research, and the proposed algorithm can reduce its power consumption.