GPU-Accelerated Monte Carlo Simulation for a Single-Photon Underwater Lidar

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 21; p. 5245
• Main Authors: Liao, Yupeng, Shangguan, Mingjia, Yang, Zhifeng, Lin, Zaifa, Wang, Yuanlun, Li, Sihui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2023
• Subjects: Algorithms; Backscattering; Central processing units; Comparative analysis; Computer simulation; CPUs; Deep sea; Design optimization; Efficiency; Energy; Graphics coprocessors; graphics processing unit; Graphics processing units; Lasers; Lidar; Lookup tables; Monte Carlo; Monte Carlo method; Monte Carlo simulation; Obstacle avoidance; Offshore platforms; Optical radar; Photons; Probability distribution; Propagation; Random processes; Remote sensing; Simulation models; single-photon underwater lidar; Technology application; Underwater; Underwater exploration; Unmanned aerial vehicles; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15215245

The Monte Carlo (MC) simulation, due to its ability to accurately simulate the backscattered signal of lidar, plays a crucial role in the design, optimization, and interpretation of the backscattered signal in lidar systems. Despite the development of several MC models for lidars, a suitable MC simulation model for underwater single-photon lidar, which is a vital ocean remote sensing technique utilized in underwater scientific investigations, obstacle avoidance for underwater platforms, and deep-sea environmental exploration, is still lacking. There are two main challenges in underwater lidar simulation. Firstly, the simulation results are significantly affected by near-field abnormal signals. Secondly, the simulation process is time-consuming due to the requirement of a high number of random processes to obtain reliable results. To address these issues, an algorithm is proposed to minimize the impacts of abnormal simulation signals. Additionally, a graphics processing unit (GPU)-accelerated semi-analytic MC simulation with a compute unified device architecture is proposed. The performance of the GPU-based program was validated using 109 photons and compared to a central processing unit (CPU)-based program. The GPU-based program achieved up to 68 times higher efficiency and a maximum relative deviation of less than 1.5%. Subsequently, the MC model was employed to simulate the backscattered signal in inhomogeneous water using the Henyey–Greenstein phase functions. By utilizing the look-up table method, simulations of backscattered signals were achieved using different scattering phase functions. Finally, a comparison between the simulation results and measurements derived from an underwater single-photon lidar demonstrated the reliability and robustness of our GPU-based MC simulation model.