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基于室内动静结合分割的射线跟踪加速方法 被引量:1

Ray tracking acceleration method based on combination of indoor dynamic and static divisions
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摘要 密闭环境的信道建模在许多应用场景中具有重要作用。在空间内障碍物较多时,传统射线跟踪算法在运算过程中会有无用的求交点次数过多的问题,使得算法的计算效率较低。为此,提出一种基于空间分割的射线跟踪加速方法。该方法根据三维空间中物体的分布情况,合理地结合静态与动态两种空间分割加速方法,大幅度减少了射线与空间内物体的求交点次数,提高了算法的计算效率。仿真分析表明,在相同预测精度的三维环境下,与原始算法对比,使用静态空间分割的射线跟踪算法随着分割等级的提升计算效率提高了至少50.2%;而与只使用静态空间分割的算法对比,使用静态与动态空间分割结合的加速方法的计算效率在已经提高的基础上至少还能提升8.9%。 Channel modeling of the closed environment plays an important role in many application scenarios.When there are many obstacles in the space,the traditional ray tracing algorithm has the problem of too many times of finding intersection points in the calculation process,which makes the algorithm calculation efficiency low.Therefore,a ray tracing acceleration method based on space division was proposed.In the method,according to the distribution of objects in threedimensional space,the static and dynamic space division acceleration methods were combined reasonably,so as to greatly reduce the number of finding intersection points between rays and objects in space,and improve the calculation efficiency of the algorithm.Simulation analysis shows that in the three-dimensional environment with the same prediction accuracy,compared with the original algorithm,the ray tracing algorithm using static space division has the calculation efficiency improved by at least 50.2%as the division level is improved;and compared with the algorithm which only uses static space division,the acceleration method based on the combination of static and dynamic space divisions has the calculation efficiency improved by at least 8.9%on the basis of the improvement above.
作者 黄一航 江虹 韩宾 HUANG Yihang;JIANG Hong;HAN Bin(School of Information Engineering,Southwest University of Science and Technology,Mianyang Sichuan 621010,China)
出处 《计算机应用》 CSCD 北大核心 2020年第10期3006-3012,共7页 journal of Computer Applications
基金 国家自然科学基金资助项目(61379005)。
关键词 密闭环境 射线跟踪 三维模型 空间分割 加速方法 closed environment ray tracing 3D model space division acceleration method
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