摘要
为提升海面场景模拟的物理真实感,本文探讨了仿真参数对海洋粗糙面模拟精确性的影响,并建立了海表模拟中仿真参数的选取准则。依据海浪谱和随机过程统计理论,采用自相关函数研究了海面相关长度随风速变化规律。通过建立海浪蒙特卡罗仿真模型,结合随机粗糙面误差分析,提出了不同风速条件下海面场景仿真参数的选取准则。研究表明:将海表模拟的采样间隔限定在顺风向相关长度的0.1~0.5倍,可显著提高海面场景模拟的精确度;而当海面仿真参数超出上述范围时,可能导致海面场景模拟失真,进而影响其视觉真实感。本文所提出的仿真参数选取标准可为开发航海模拟器提供技术支撑。
To enhance the physical realism of sea surface simulation,this study explores the influences of distinct simulation parameters on the surface′s simulation accuracy and establishes criteria for selecting appropriate simulation parameters when simulating the sea surfaces.According to wave spectra and random process statistics theory,the autocorrelation function is employed to investigate the variation in the correlation length of sea surfaces with the change of wind velocity.Through the establishment of a Monte-Carlo simulation model and combining it with error analysis in generating random rough surfaces,the paper proposes criteria for selecting simulation parameters for sea surface scenes under varying wind velocities.The results indicate that restricting the sampling interval within the range of 0.1~0.5 times the correlation length along the downwind direction can significantly enhance the accuracy of sea surface simulation.In contrast,the existence of sea surface simulation parameters exceeding this range may cause distortions in the simulation,thereby impacting the visual realism.The proposed simulation parameter selection criteria can provide technical support for the development of marine simulators.
作者
曹宝根
孙强
赵禧金
许镇
CAO Baogen;SUN Qiang;ZHAO Xijin;XU Zhen(Navigation College,Jimei University,Xiamen 361021,China;Department of Electronic Information Engineering,Shantou University,Shantou 515063,China)
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2024年第8期1476-1487,共12页
Journal of Harbin Engineering University
基金
国家自然科学基金项目(42101398)
福建省中青年教师教育科研项目(JAT200275)
汕头大学卓越人才计划科研启动经费项目(NTF20023).
关键词
海面场景模拟
航海模拟器
海浪谱
自相关函数
相关长度
参数选取准则
随机过程
蒙特卡罗仿真
sea surface simulation
maritime simulator
wave spectrum
autocorrelation function
correlation length
parameter selection criteria
random process
Monte-Carlo simulation