Article(id=1239206944062362210, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239206938739798226, articleNumber=null, orderNo=null, doi=10.12347/j.ycyk.20240712001, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720713600000, receivedDateStr=2024-07-12, revisedDate=1726329600000, revisedDateStr=2024-09-15, acceptedDate=null, acceptedDateStr=null, onlineDate=1773379558815, onlineDateStr=2026-03-13, pubDate=1736870400000, pubDateStr=2025-01-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773379558815, onlineIssueDateStr=2026-03-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773379558815, creator=13701087609, updateTime=1773379558815, updator=13701087609, issue=Issue{id=1239206938739798226, tenantId=1146029695717560320, journalId=1238841944844054536, year='2025', volume='46', issue='1', pageStart='1', pageEnd='125', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773379557547, creator=13701087609, updateTime=1773379632176, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1239207251815223477, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239206938739798226, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1239207251815223478, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239206938739798226, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=23, endPage=29, ext={EN=ArticleExt(id=1239206944272077416, articleId=1239206944062362210, tenantId=1146029695717560320, journalId=1238841944844054536, language=EN, title=A Novel Indoor Ray Tracing Method, columnId=1239206939612213461, journalTitle=Journal of Telemetry, Tracking and Command, columnName=Antenna Servo and Feed Technology, runingTitle=null, highlight=null, articleAbstract=

As the existing ray tracing algorithms exhibit low efficiency in indoor scenarios, this paper presents a novel ray tracing approach for computing the electromagnetic field within a building. Firstly, a matrix is incorporated to denote the visibility of all surfaces. Among all candidate rays between a pair of source and field points, the least likely ones are eliminated by the visibility matrix. The remaining rays are then analyzed using the conjugate gradient method to precisely determine the ray path. Subsequently, ray-object intersection tests are carried out, which are also expedited by the visibility matrix. Eventually, if the ray is present, the electromagnetic field is calculated via the uniform theory of diffraction (UTD). This new ray tracing algorithm can handle all types of rays, such as the reflected, diffracted, and refracted ones. Hence, it is more flexible compared to the image method. An example of a house demonstrates that it is more accurate and faster than WinProp in indoor scenarios.

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针对现有射线寻迹方法在室内场景应用时效率低下的问题,本文研究一种射线追踪的新方法,用于计算建筑物内部的电磁场分布。首先,引入一个可见面矩阵来描述所有平面的遮挡关系。在连接源点和场点的所有可能射线中,将最不可能的那些射线直接通过该矩阵排除掉,而剩余的射线通过严格的共轭梯度法进行识别,从而确定射线的准确路径。接着,采用一致性几何绕射理论计算每一条射线的电磁场。这种通用的射线追踪算法能够对任意反射、折射和绕射射线进行分析,因此比镜像法更灵活。最后,通过计算一栋房子内电磁场分布表明:本文方法在室内应用场景中比WinProp(电磁波传播仿真软件)更快更准确。

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袁浩波 1980年生,博士,副教授。

侯雨辰 1999年生,硕士研究生。

杨普 2000年生,硕士研究生。

李莎莎 1984年生,博士,高级工程师。

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一种新的室内射线追踪方法
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袁浩波 1 , 侯雨辰 1 , 杨普 1 , 李莎莎 2
遥测遥控 | 天伺馈技术专栏 2025,46(1): 23-29
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遥测遥控 | 天伺馈技术专栏 2025, 46(1): 23-29
一种新的室内射线追踪方法
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袁浩波1, 侯雨辰1, 杨普1, 李莎莎2
作者信息
  • 1西安电子科技大学 西安 710071
  • 2北京航天长征飞行器研究所 北京 100076
  • 袁浩波 1980年生,博士,副教授。

    侯雨辰 1999年生,硕士研究生。

    杨普 2000年生,硕士研究生。

    李莎莎 1984年生,博士,高级工程师。

A Novel Indoor Ray Tracing Method
Haobo YUAN1, Yuchen HOU1, Pu YANG1, Shasha Li2
Affiliations
  • 1.Xidian University, Xi'an 710071, China
  • 2.Beijing Institute of Space Long March Vehicle, Beijing 100076, China
出版时间: 2025-01-15 doi: 10.12347/j.ycyk.20240712001
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针对现有射线寻迹方法在室内场景应用时效率低下的问题,本文研究一种射线追踪的新方法,用于计算建筑物内部的电磁场分布。首先,引入一个可见面矩阵来描述所有平面的遮挡关系。在连接源点和场点的所有可能射线中,将最不可能的那些射线直接通过该矩阵排除掉,而剩余的射线通过严格的共轭梯度法进行识别,从而确定射线的准确路径。接着,采用一致性几何绕射理论计算每一条射线的电磁场。这种通用的射线追踪算法能够对任意反射、折射和绕射射线进行分析,因此比镜像法更灵活。最后,通过计算一栋房子内电磁场分布表明:本文方法在室内应用场景中比WinProp(电磁波传播仿真软件)更快更准确。

共轭梯度法  /  电磁场  /  射线追踪  /  一致性几何绕射理论

As the existing ray tracing algorithms exhibit low efficiency in indoor scenarios, this paper presents a novel ray tracing approach for computing the electromagnetic field within a building. Firstly, a matrix is incorporated to denote the visibility of all surfaces. Among all candidate rays between a pair of source and field points, the least likely ones are eliminated by the visibility matrix. The remaining rays are then analyzed using the conjugate gradient method to precisely determine the ray path. Subsequently, ray-object intersection tests are carried out, which are also expedited by the visibility matrix. Eventually, if the ray is present, the electromagnetic field is calculated via the uniform theory of diffraction (UTD). This new ray tracing algorithm can handle all types of rays, such as the reflected, diffracted, and refracted ones. Hence, it is more flexible compared to the image method. An example of a house demonstrates that it is more accurate and faster than WinProp in indoor scenarios.

Conjugate gradient method  /  Electromagnetic field  /  Ray tracing  /  Uniform theory of diffraction
袁浩波, 侯雨辰, 杨普, 李莎莎. 一种新的室内射线追踪方法. 遥测遥控, 2025 , 46 (1) : 23 -29 . DOI: 10.12347/j.ycyk.20240712001
Haobo YUAN, Yuchen HOU, Pu YANG, Shasha Li. A Novel Indoor Ray Tracing Method[J]. Journal of Telemetry, Tracking and Command, 2025 , 46 (1) : 23 -29 . DOI: 10.12347/j.ycyk.20240712001
无线网络的室内部署需要确定天线的具体坐标,可以采用多种方法实现。首先,可以采用无线信道传播模型[1,2]进行估计,但是它仅对特定的环境和条件有效,而且精度较低;其次,通过电磁测量来确定天线的坐标是最可靠的,但是其成本高昂,实际上并不可行。目前,常常将射线追踪算法作为预测室内电波传播的一种有效方法[3-9]。射线追踪方法的主要任务是确定射线从源点到场点的所有具体路径。然而,射线追踪对于室内环境来说是极其困难的。因为室内可能存在大量的射线,每一条射线都可能由多次反射、折射和绕射混合组成。
根据费马原理[10],光沿着所需时间最短的路径传播。从理论上讲,射线的具体路径可以通过最小化其光程来确定,也就是一个优化问题。然而优化属于数值方法,耗时很长,因此并没有应用于现有的射线追踪方法中。实际上,费马原理推导出了反射、折射和绕射定律,这些定律对应的解析公式可以方便地进行射线追踪,对应的方法有两大类:镜像法[3-5]和弹跳射线法(SBR)[6-9]
镜像法利用镜像原理计算出射线的精确路径。如果有M个反射面,且只考虑N次反射,则镜像总数为。由于室内环境中反射面数目M往往较大,此时镜像法的计算速度非常慢。弹跳射线法则是一种速度较快的方法。它将天线发射的场划分为若干条射线管,追踪每一条射线管与其他平面相交的情况,计算反射和折射导致的电场衰减值,最终得到场点的电场数值。弹跳射线法一般无法得到准确的相位信息,因此精度并不高[11]
在过去的几十年里,人们采用许多技术来加速弹跳射线法的射线追踪过程。采用可见性图(Visibility Graph)[12,13]可以加速射线与平面相交的分析。但是当相交的次数很多时,建立可见性图的过程将极其复杂而缓慢。空间分割法(Space Division)[14-18]将整个传播空间分割成小方块,然后确定它们所有的相邻信息。这种“分而治之”的策略能快速排除了相交过程中涉及的大部分平面。最近,人们将基于GPU(图形处理器)的射线追踪引擎[19,20]用于模拟电波传播,可以使计算速度提高数百倍。
总体来看,弹跳射线法比镜像法更快,但精度较低。而镜像法虽然精度较高,但是只能分析反射射线,不能分析绕射和折射射线。基于此,本文针对室内环境提出了一种更精确的射线追踪算法。该方法综合采用了三种技术:(1) 利用共轭梯度法(CG)[21]优化光程,通过数值方法精确计算源点和场点之间射线传播的路径。(2) 类似可见性图,引入一种可见面矩阵来排除大部分不可能的路径,使得共轭梯度法只需要分析少数路径。(3) 使用暴力算法在所有可能的路径中搜索有效的路径,从而确保不遗漏任何一条射线。数值仿真的结果表明:该算法比弹跳射线法和镜像法更准确,有时甚至比弹跳射线法更快。
本文的方法只能适用于结构比较规则的室内建筑物,即建筑物内没有曲面而只有平面。因为射线通过曲面的光程是个复杂的非线性函数,存在多个局部最优解,而共轭梯度法难以求解这种问题。尽管本文的方法适用于分析各种类型的射线,但是涉及绕射时的公式极其冗长,故而下面只给出反射和折射射线对应的公式。
图1中连接两点rArB的线段可以表示为
由四个顶点(r11r21r12r22)构成一个双线性平面,其上任意点P的坐标为:
双线性平面是一个略微弯曲的四边形,但如果四个顶点共面,则它变为平面四边形。如果一条线段与双线性平面相交,它们必须满足以下方程。
该方程有解析解(u,v,t)。如果所有参数均满足(u,v,t)∈[-1,1],则线段与平面相交;否则,线段不与平面相交。
任何一条射线路径都可能包含多条不同类型的射线,包括直射、反射、折射、绕射射线及其排列组合。作为一个简单的例子,图2给出从A点经过N个面到达B点的射线,称为N阶射线。这里每个表面都是两种不同介质之间的界面,介质折射率分别为n1,n2,…,nN,nN+1
为了确定所有交点的坐标,可以根据费马原理计算光程的极小值。
目标函数L(u,v)的偏导数为
式中ni为介质的反射指数。对于一些非常简单的问题,如只有一个或两个面的反射,式(4)可以解析求解。但是绝大多数实际问题必须通过数值优化方法来解决。幸运的是,当所有的面都是平面时,式(4)属于一个无约束二次规划问题,具有唯一解,而且这种唯一解可以用共轭梯度法快速求出。
共轭梯度法需要以下信息:①每个曲面上顶点的坐标;②每个面上两种介质的折射率;③射线路径上交点的顺序:P0,P1,P2,…,PN,PN+1;④计算目标函数及其导数的子函数。共轭梯度法逐步迭代,最终使目标函数的梯度逼近零。在数值实验中,共轭梯度法一般在2N次迭代后收敛到准确结果。接着进行判断,当所有参数都满足(ui,vi)∈[-1,1]时,上述模型中才存在有效路径P0P1P2…→PN+1
图3给出的实际环境中有M个面,但是仅仅考虑其中的N<M阶射线,那么总共有(M+1)N种可能。所谓的暴力算法,就是采用前面所述的共轭梯度法分析每一条可能的射线。这种方法十分严格,不会漏掉有效的射线,但缺点是速度非常慢。实际上,大多数可能的射线是无效的,在共轭梯度法执行之前可以通过多种策略将其排除,从而大大加快射线追踪的速度。
引入了一种类似于可见性图的可见面矩阵来加速光线追踪。例如,图4显示了一对平面S1S2,它们被另一个平面S3完全分开。从S1S2的射线是不可能的,不需要用共轭梯度法处理。下面的算法可以确定S1S2之间的可见性。将S1的顶点和S2的顶点用线段连接,可以用前述A部分的方法判断线段是否与S3相交。这样的线段一共有16条。如果所有线段都与S3相交,则可以判断S1S2S3完全遮挡,即两个平面彼此不可见。相反,如果有任何一条不与S3相交,则S1S2彼此可见。
图5给出有两个房间的一栋房子示意图。为简单起见,只考虑三个面S1S2S3RF分别表示源点和场点。此时很容易得到如图6所示的可见面矩阵,图中×为不可见,√为可见。图7列出了从RF的所有22种可能的射线。例如图6中的射线RS1S3F是无效的,因为S1S3是不可见的。此外,射线RS1S3F可能是有效的,因为任何一对相邻的物体对彼此都是可见的。这条射线需要后续采用共轭梯度法处理以找到交叉点,并确定其是否真的存在。最后,图7中排除了20种不可能的射线,只剩下2种可能的射线。因此,可见面矩阵极大地加快了射线追踪的速度。
①输入建筑物的数据。(R,F)为源点和场点的坐标;M为光线穿过的最大面数或边数;N为建筑物表总面数;n1,n2,…nN为介质的折射率。
②将R,S1,S2,…SN,F重新排序为0,1,2,…,N,N+1,然后用1.4节给出的方法得到可见面矩阵V(N+2)×(N+2)
③对于所有可能的射线i=0,1,2,…(N+1)M
④第i条可能的射线是。确定对象的下标:0→j1j2,…jMN+1。找到可见面矩阵中的元素:V(0,j1),V(j1,j2),…,V(jM,N+1)。如果上述任何一个矩阵元素为假,则第i条射线不存在,转到步骤③;如果上述所有矩阵元素都为真,转到步骤⑤。
⑤用共轭梯度法求解公式(4)中第i条射线的优化问题。如果解是无效的,则第i条射线不存在,转到步骤③;反之,求出射线上所有的相交点RP1P2,…PMF,转到步骤⑥。
⑥如果线段PkPk+1与一个对PkPk+1可见的面相交,则第i条射线不存在,转到步骤③。反之,第i条射线存在,转到步骤③。
一旦完成了室内环境的射线追踪,则使用一致性几何绕射理论计算给定场点处的电磁场[22,23]。以如图8所示的理想导体劈型结构为例,在任意观察点处的总场由直射场、反射场和绕射场构成:
图8中的空间被入射阴影边界(ISB)和反射阴影边界(RSB)划分出三个区域,各部分的总场为:
各种场的计算公式参考文献[21,22]。
图9给出了一套房屋结构的俯视图,假定墙体材料的参数为:εr=5.0,μr=1.0,σ=0.001 s/m。偶极子天线的工作频率为12 GHz,辐射功率为l W,位于(3 m, 8 m, 2.9 m)处。此处只考虑一到四阶射线。图10给出了到达某个场点(7 m, 2.4 m, 1.2 m)的所有前三阶射线。从图11图12可以看出,本文方法计算的室内电场与商业软件WinProp计算的结果基本一致。图13给出了两种方法的差别,其均方根值为6.36 dB。此外,除了墙壁上的一些点外,绝大多数点的差别都小于5 dB。作为常规的弹跳射线法,商业软件Win-Prop通过一个衰减因子简单地考虑墙壁对场的影响。而本文方法将墙体视为两个平面,并严格计算射线的路径,所得到的墙体的场比WinProp的结果看起来更合理。最后,WinProp计算所有48 000个场点花费了16 584秒,而本文方法只需10 882秒。
本文提出的室内射线追踪方法结合了可见面矩阵和共轭梯度法两种技术,能够准确分析各种类型的射线路径,而且几乎不会遗漏任何射线。它比现有的镜像法更灵活,也比弹跳射线法更快。这种方法目前只能分析平面结构,将其推广到曲面上比较困难。此外,后续还将通过混合射线追踪方法[24]排除更多的候选射线,从而进一步提高计算效率。
  • 国家自然科学基金(U2241203)
  • 国家自然科学基金(62271365)
  • 陕西省重点研发计划(2024GX-YBXM-232)
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2025年第46卷第1期
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doi: 10.12347/j.ycyk.20240712001
  • 接收时间:2024-07-12
  • 首发时间:2026-03-13
  • 出版时间:2025-01-15
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  • 收稿日期:2024-07-12
  • 修回日期:2024-09-15
基金
国家自然科学基金(U2241203)
国家自然科学基金(62271365)
陕西省重点研发计划(2024GX-YBXM-232)
作者信息
    1西安电子科技大学 西安 710071
    2北京航天长征飞行器研究所 北京 100076
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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