Article(id=1212062514221805992, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, articleNumber=null, orderNo=null, doi=10.12284/hyxb2023122, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1662048000000, receivedDateStr=2022-09-02, revisedDate=1681833600000, revisedDateStr=2023-04-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1766907822422, onlineDateStr=2025-12-28, pubDate=1696003200000, pubDateStr=2023-09-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766907822422, onlineIssueDateStr=2025-12-28, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766907822422, creator=13701087609, updateTime=1766907822422, updator=13701087609, issue=Issue{id=1212062510887342132, tenantId=1146029695717560320, journalId=1149651085930835976, year='2023', volume='45', issue='9', pageStart='1', pageEnd='188', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766907821628, creator=13701087609, updateTime=1766924706207, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1212133329994904375, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1212133329994904376, tenantId=1146029695717560320, journalId=1149651085930835976, issueId=1212062510887342132, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=168, endPage=176, ext={EN=ArticleExt(id=1212062514540573109, articleId=1212062514221805992, tenantId=1146029695717560320, journalId=1149651085930835976, language=EN, title=Iterative correction method of beam incident angle for ultra-short baseline underwater acoustic positioning, columnId=1194652705852465724, journalTitle=Haiyang Xuebao, columnName=Article, runingTitle=null, highlight=null, articleAbstract=

The inhomogeneity of the seawater medium causes the refraction effect in the sound wave propagation process. The ultra-short baseline system using the planar acoustic array will be affected by this phenomenon during the measurement process, which will cause large errors in the measurement results. The sound ray tracking method is usually used to correct the sound ray by using the measured sound velocity profile. Accurate beam incident angle is the prerequisite to ensure the accuracy of sound ray tracking, but the ultra-short baseline system does not directly measure the beam incident angle but uses the approximate incident angle derived from the acoustic phase difference for sound ray tracking will cause a certain loss of accuracy. To solve the above problems, this paper proposes an iterative correction method of beam incidence angle for ultra-short baseline underwater acoustic positioning. Based on constant gradient acoustic ray tracking, the iterative calculation relationship between beam incidence angle and propagation time is constructed, the Aitken acceleration method is used to quickly solve the nonlinear equation of the beam incidence angle. Simulation experiments prove that the method proposed in this paper can accurately calculate the beam incident angle and target position, and effectively eliminate the influence of refraction effects on ultra-short baseline underwater positioning.

, correspAuthors=Jinjin Wei, authorNote=null, correspAuthorsNote=null, copyrightStatement=Copyright © 2023 Pratacultural Science. All rights reserved., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Xingguo Gao, Jinjin Wei, Mingzhen Xin, Zengliang Chang, Chaoyi Wu, Meng Qu), CN=ArticleExt(id=1212062517887627856, articleId=1212062514221805992, tenantId=1146029695717560320, journalId=1149651085930835976, language=CN, title=超短基线水声定位的波束入射角迭代修正方法, columnId=1149698756456657529, journalTitle=海洋学报, columnName=论文, runingTitle=null, highlight=null, articleAbstract=

海水介质的不均匀性导致声波传播过程会产生折射效应,采用平面声基阵的超短基线系统在测量过程中会受到该现象的影响,从而使测量结果产生较大的误差,通常采用声线跟踪的方法利用实测声速剖面进行声线修正。准确的波束入射角是确保声线跟踪精度的前提,超短基线系统是利用声学相位差推算得到近似波束入射角,而利用近似波束入射角进行声线跟踪会造成一定的精度损失。针对上述问题,本文提出了一种超短基线水声定位的波束入射角迭代修正方法,基于常梯度声线跟踪构建起了波束入射角与传播时间的迭代计算关系,采用埃特金加速法实现了波束入射角的非线性方程快速解算。通过仿真实验证明本文提出方法能够实现波束入射角与目标位置的准确计算,有效消除了折射效应对超短基线水下定位的影响。

, correspAuthors=卫进进, authorNote=null, correspAuthorsNote=
*卫进进(1997-),男,山西省运城市人,助理工程师,主要研究方向为海洋导航与定位。E-mail:
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高兴国(1984-),男,山东省潍坊市人,高级工程师,主要研究方向为海洋测绘。E-mail:

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高兴国(1984-),男,山东省潍坊市人,高级工程师,主要研究方向为海洋测绘。E-mail:

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高兴国(1984-),男,山东省潍坊市人,高级工程师,主要研究方向为海洋测绘。E-mail:

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Statistical table of simulation results

, figureFileSmall=null, figureFileBig=null, tableContent=
计算方法σx/mσy/mσp/m计算时间/s
注:σxx方向定位标准差;σyy方向定位标准差;σp为平面位置定位标准差。
平均声速法(c = 1 490 m/s)4.074.025.730.2
平均声速法(c = 1 500 m/s)2.742.733.870.2
平均声速法(c = 1 510 m/s)6.216.128.720.2
常梯度声线跟踪−
近似波束入射角法
2.342.363.3222.2
常梯度声线跟踪−
波束入射角搜索法
1.491.492.11980.1
常梯度声线跟踪−
波束入射角牛顿迭代法
1.471.492.1056.7
常梯度声线跟踪−
波束入射角埃特金加速迭代法
1.471.492.1013.9
), ArticleFig(id=1215325229266681910, tenantId=1146029695717560320, journalId=1149651085930835976, articleId=1212062514221805992, language=CN, label=表1, caption=

仿真结果统计表

, figureFileSmall=null, figureFileBig=null, tableContent=
计算方法σx/mσy/mσp/m计算时间/s
注:σxx方向定位标准差;σyy方向定位标准差;σp为平面位置定位标准差。
平均声速法(c = 1 490 m/s)4.074.025.730.2
平均声速法(c = 1 500 m/s)2.742.733.870.2
平均声速法(c = 1 510 m/s)6.216.128.720.2
常梯度声线跟踪−
近似波束入射角法
2.342.363.3222.2
常梯度声线跟踪−
波束入射角搜索法
1.491.492.11980.1
常梯度声线跟踪−
波束入射角牛顿迭代法
1.471.492.1056.7
常梯度声线跟踪−
波束入射角埃特金加速迭代法
1.471.492.1013.9
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超短基线水声定位的波束入射角迭代修正方法
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高兴国 1 , 卫进进 2, 3, * , 辛明真 2, 4 , 常增亮 1 , 吴超逸 2 , 曲萌 1
海洋学报 | 论文 2023,45(9): 168-176
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海洋学报 | 论文 2023, 45(9): 168-176
超短基线水声定位的波束入射角迭代修正方法
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高兴国1 , 卫进进2, 3, * , 辛明真2, 4, 常增亮1, 吴超逸2, 曲萌1
作者信息
  • 1 山东电力工程咨询院有限公司,山东 济南 250013
  • 2 山东科技大学 测绘与空间信息学院,山东 青岛 266590
  • 3 浙江省水利河口研究院(浙江省海洋规划设计研究院),浙江 杭州 310020
  • 4 自然资源部海洋测绘重点实验室,山东 青岛 266590
  • 高兴国(1984-),男,山东省潍坊市人,高级工程师,主要研究方向为海洋测绘。E-mail:

通讯作者:

*卫进进(1997-),男,山西省运城市人,助理工程师,主要研究方向为海洋导航与定位。E-mail:
Iterative correction method of beam incident angle for ultra-short baseline underwater acoustic positioning
Xingguo Gao1 , Jinjin Wei2, 3, * , Mingzhen Xin2, 4, Zengliang Chang1, Chaoyi Wu2, Meng Qu1
Affiliations
  • 1Shandong Electric Power Engineering Consulting lnstitute Corp., LTD, Jinan 250013, China
  • 2College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
  • 3Zhejiang Institute of Hydraulics and Estuary (Zhejiang Institute of Marine Planning and Design), Hangzhou 310020, China
  • 4Key Laboratory of Oceanic Surveying and Mapping, Ministry of Natural Resources, Qingdao 266590, China
出版时间: 2023-09-30 doi: 10.12284/hyxb2023122
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海水介质的不均匀性导致声波传播过程会产生折射效应,采用平面声基阵的超短基线系统在测量过程中会受到该现象的影响,从而使测量结果产生较大的误差,通常采用声线跟踪的方法利用实测声速剖面进行声线修正。准确的波束入射角是确保声线跟踪精度的前提,超短基线系统是利用声学相位差推算得到近似波束入射角,而利用近似波束入射角进行声线跟踪会造成一定的精度损失。针对上述问题,本文提出了一种超短基线水声定位的波束入射角迭代修正方法,基于常梯度声线跟踪构建起了波束入射角与传播时间的迭代计算关系,采用埃特金加速法实现了波束入射角的非线性方程快速解算。通过仿真实验证明本文提出方法能够实现波束入射角与目标位置的准确计算,有效消除了折射效应对超短基线水下定位的影响。

超短基线  /  常梯度声线跟踪  /  波束入射角  /  声速剖面  /  埃特金加速法

The inhomogeneity of the seawater medium causes the refraction effect in the sound wave propagation process. The ultra-short baseline system using the planar acoustic array will be affected by this phenomenon during the measurement process, which will cause large errors in the measurement results. The sound ray tracking method is usually used to correct the sound ray by using the measured sound velocity profile. Accurate beam incident angle is the prerequisite to ensure the accuracy of sound ray tracking, but the ultra-short baseline system does not directly measure the beam incident angle but uses the approximate incident angle derived from the acoustic phase difference for sound ray tracking will cause a certain loss of accuracy. To solve the above problems, this paper proposes an iterative correction method of beam incidence angle for ultra-short baseline underwater acoustic positioning. Based on constant gradient acoustic ray tracking, the iterative calculation relationship between beam incidence angle and propagation time is constructed, the Aitken acceleration method is used to quickly solve the nonlinear equation of the beam incidence angle. Simulation experiments prove that the method proposed in this paper can accurately calculate the beam incident angle and target position, and effectively eliminate the influence of refraction effects on ultra-short baseline underwater positioning.

ultra-short baseline  /  constant gradient sound ray tracing  /  incident beam angles  /  sound velocity profile  /  Aitken acceleration method
高兴国, 卫进进, 辛明真, 常增亮, 吴超逸, 曲萌. 超短基线水声定位的波束入射角迭代修正方法. 海洋学报, 2023 , 45 (9) : 168 -176 . DOI: 10.12284/hyxb2023122
Xingguo Gao, Jinjin Wei, Mingzhen Xin, Zengliang Chang, Chaoyi Wu, Meng Qu. Iterative correction method of beam incident angle for ultra-short baseline underwater acoustic positioning[J]. Haiyang Xuebao, 2023 , 45 (9) : 168 -176 . DOI: 10.12284/hyxb2023122
水下定位导航是海洋开发活动的基础和保障[1-4],依靠水声信号在水体中良好的传播特性,发展出了以超短基线系统(Ultra Short Baseline System, USBL)、短基线系统(Short Baseline System, SBL)、长基线系统(Long Baseline System, LBL)和GNSS-A浮标系统(GNSS-Acoustic Buoys System, GAB)[5-7]为代表的水声定位系统。与其他几种基于距离交会定位原理的水声定位系统不同,超短基线系统采用测距测向定位模式,具有高度集成、方便小巧、操作简单且造价低廉等优势[8-11],已经在科学调查、工程实践中得到广泛应用。随着声学换能器研制技术的不断进步,制约水声定位精度的原因已经由硬件测量误差转变为定位模型与误差模型的不完善,其中海水声速变化引起的折射效应是主要影响因素之一[12-14]。折射效应本质上是指声波受声速变化导致传播路径为连续弯曲曲线的现象,通常需要结合实测声速剖面利用声线跟踪的方法还原声波的实际传播路径,从而实现对水声距离观测值的改正[15-16]
常梯度声线跟踪是目前应用广泛且精度较高的声线跟踪方法[17-20],陆秀平等[21]对常梯度声线跟踪的弦长积分和弧长积分进行了对比分析。Mary和Willian[22],孙革[23]及赵建虎和刘经南[24]提出了常梯度声线跟踪数值计算算法,在声速剖面分层较多的情况下可解算得到精度较高的距离改正值。Geng和Zielinski[25]基于声速剖面积分面积相等的原则提出了等效声速剖面法,有效提高了声线跟踪计算效率,但也存在一定的精度损失。吴德明[26]提出了一种单差水声定位的声线修正迭代法,对超短基线的声线跟踪和定位解算有一定的参考价值。Sun等[27]提出一种基于USBL的声速修正算法,根据实测声速剖面构建有效声速表进行USBL实时定位解算。Yang等[28]提出了一种测距误差拟合的声速误差改正方法,实现了声速剖面未知情况下的高精度定位误差改正。王振杰等[29]提出一种针对水声定位的大入射角声线跟踪方法,解决了在波束入射角较大的情况下迭代发散的问题。Xin等[30]和辛明真[31]提出了一种到达时间(Time of Arrival, TOA)/到达角度(Angle of Arrival, AOA)水声定位系统,通过将等效声速梯度和目标坐标分别作为未知参数进行估计解算,实现了高精度的声线跟踪和定位解算。
声线跟踪的前提是波束入射角准确已知,但由于超短基线利用相位差或时延差计算方位角的方式本身就存在一定的误差,加之换能器载体的姿态变化也会影响到波束入射角的准确计算,因此严格意义上来说超短基线无法直接测量得到准确的波束入射角。对于上述问题,实际应用中无非两种处理方法,一是直接采用平均声速计算距离观测值并定位计算,显然是一种简单的近似计算方法;二是利用相位差或时延差计算近似波束入射角,并采用近似波束入射角进行声线跟踪和定位计算,但也必然存在一定的精度损失。为此,本文提出了一种超短基线的波束入射角迭代修正声线跟踪方法,通过波束入射角和目标位置的渐次修正实现高精度的声线跟踪和定位解算,改进方法对研究同类水下高精度导航定位工作具有一定的借鉴意义。
超短基线系统通过测量目标至换能器各个声学单元的相位差,采用测距测向原理确定水下目标位置。以目前较为常见的由3个声学单元按平面垂直分布构成的声学基准为例进行分析研究。如图1所示,设换能器中的3个声学单元分别为O、A、B,OA和OB间的基线长度分别为dxdy,目标信号传播至系统测量声学单元的相位分别为$ \tau$$ \tau_a$$ \tau_b$,而OA、OB间的相位差为${\tau _x} = \tau - {\tau _a}$${\tau _y} = \tau - {\tau _b}$
当海水声速为常值c时,目标至换能器的斜距ρ可表示为
$ \rho = ct/2, $
式中,t为换能器发射声波到接收声波的时间。由空间几何关系可以得到声单元O和目标连线与xy轴的夹角余弦值为
$ \left\{ \begin{gathered} {\text{cos}}\;{\theta _x} = \lambda {\tau _x}/2 {\text{π}} {d_x} \\ {\text{cos}}\;{\theta _y} = \lambda {\tau _y}/2 {\text{π}} {d_y} \\ \end{gathered} \right.\text{,} $
式中,θxθy为换能器处声线传播方向分别与x轴、y轴的夹角;λ为声波波长。此时的波束入射角,即声线在声单元O处的传播方向线与z轴的夹角,可表示为
${\text{cos}}\;{\theta _0} = \sqrt {1-{\text{cos}}\;{\theta^2 _x}- {\text{cos}}\;{\theta _y^2} }$
信标P坐标可以表示为
$ \left\{ \begin{gathered} {x_t} = \rho \cdot {\text{cos}}\;{\theta _x} = ct\lambda {\tau _x}/4 {\text{π}} {d_x} \\ {y_t} = \rho \cdot {\text{cos}}\;{\theta _y} = ct\lambda {\tau _y}/4 {\text{π}} {d_y} \\ {{\textit{z}}_t} = \sqrt {{\rho ^2} - x_t^2 - y_t^2} \\ \end{gathered} \right.. $
由式(4)可知,只有当距离观测值${s_k} = \sqrt {\Delta x_k^2 + \Delta {\textit{z}}_k^2}$为换能器与水下目标点间的直线距离时,才能保证水下目标定位的精度。但海水为非均匀介质体,海水中的声速存在时空上的变化,因此声速c显然不是一个常值,而声速变化会使得声波沿传播方向发生折射。为了准确还原声波的实际传播路径并得到准确的距离观测值,通常采用常梯度声线跟踪方法进行折射改正。
图2所示,若第k层对应声速区间为(ck, ck+1),波束入射角为θkk = 0, 1,···, n,根据射线声学理论,认为声线在常梯度情况下传播轨迹为圆弧,圆弧半径Rk
$ R_k=1/|pg_k| \text{,} $
式中,p为Snell常数;gk为层内声速梯度,可分别表示为
$ p= {\rm{sin}}\;{\theta _k}/c_k \text{,} $
$ g_k =(c_{k+1}-c_k)/({\textit{z}} _{k+1}-{\textit{z}} _k)\text{,} $
则第k层声线的垂向距、侧向距可分别表示为
$ \Delta {\textit{z}} _k = ({\rm{sin}}\;\theta _{k+1}-{\rm{sin}}\;\theta_ k) \text{,} $
$ \Delta x_k = ({\rm{cos}}\;\theta _{k}-{\rm{cos}}\;\theta_ {k+1}) \text{,} $
改正后的距离为
$ {s_k} = \sqrt {\Delta x_k^2 + \Delta {\textit{z}} _k^2} . $
声波沿圆弧从sk传播到sk+1所需要的时间tk可表示为
$ t_k ={\rm{ln}}[{\rm{tan}}(\theta_{k+1}/2)/{\rm{tan}}(\theta_k/2)]/g_k, $
反推得由tk计算波束入射角θk+1的公式为
$ \theta_{k+1}=2 \;{\rm{arctan}}[{\rm{e}}^{t_kg_k}{\rm{tan}}(\theta_k/2)]. $
结合上述推导可知,常梯度声线跟踪的前提是波束入射角θ0、声速梯度g以及时间延迟t已知。对于超短基线系统而言,时间延迟t通过直接观测获得,声速梯度g可由实测声速剖面确定。而波束入射角θ0并非通过测量直接得到的,而是在顾及测量载体姿态变化的基础上利用式(2)、式(3)推算得到,因此其必然存在较大的误差,本文将由此得到的波束入射角称为近似波束入射角,下面将对超短基线声线跟踪进行误差分析和方法改进。
对超短基线近似波束入射角的误差进行分析,如图3a所示,当水体中的声速为常值的时候,声波沿直线传播,此时不存在声波折射效应也无需进行声线跟踪。如图3b所示,实际声线受折射效应影响表现为连续弯曲的曲线,声线跟踪是在波束入射角θ0已知的情况下,利用相位差观测值和声速剖面确定声线的实际路径s和直线距离ρ图3c表示超短基线系统并非对波束入射角进行了直接测量,而是利用角度间的关系计算得到近似波束入射角,近似的波束入射角${\theta }'_0 $会使声线跟踪也产生较大误差,而且这种误差影响程度与实际声速剖面有关,且通常会随着传播距离的增大而不断累计。图3d表示在计算误差影响基础上,近似波束入射角还与载体姿态的测量精度直接相关,在没有准确的姿态传感器或姿态测量精度较低的情况下,对声线跟踪精度会产生较大的影响。
由此可以将超短基线的实际波束入射角表示为
$ \begin{split} {\theta _0} &= f\left( {\lambda ,{\tau _x},{\tau _y},{\theta _a}} \right) \\ & ={\rm{arccos}}\left[ \sqrt {1 - {\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)^2} \right] + {\theta _a} \end{split} . $
根据误差传播律可以得到波束入射角误差
$ \begin{split} \Delta \theta _{_0}^2 = & {\left( {\frac{{\partial f}}{{\partial \lambda }}\Delta \lambda } \right)^2} + {\left( {\frac{{\partial f}}{{\partial {\tau _x}}}\Delta {\tau _x}} \right)^2} + \\ & {\left( {\frac{{\partial f}}{{\partial {\tau _y}}}\Delta {\tau _y}} \right)^2} + {\left( {\frac{{\partial f}}{{\partial {\theta _a}}}\Delta {\theta _a}} \right)^2} \\ \end{split} \text{,} $
式中,
$ \begin{split} \frac{{\partial f}}{{\partial \lambda }} = \; &\lambda \left[ {\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 + \tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]/ \\ & {\left[ {1 - {\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}}/ \\ &{\left[{{\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}} \end{split} \text{,} $
$ \begin{split} \frac{{\partial f}}{{\partial {\tau _x}}} =\; & \tau _x^{}{\lambda ^2}/\left( {2{\text{π}} {d_x}} \right)_{}^2/ \\ & {\left[ {1 - {\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}}/ \\ &{\left[{{\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}} \end{split} \text{,} $
$ \begin{split} \frac{{\partial f}}{{\partial {\tau _y}}} = &\; \tau _y^{}{\lambda ^2}/\left( {2{\text{π}} {d_y}} \right)_{}^2/ \\ &{\left[ {1 - {\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}}/ \\ &{\left[ {{\lambda ^2}\tau _x^2/\left( {2{\text{π}} {d_x}} \right)_{}^2 - {\lambda ^2}\tau _y^2/\left( {2{\text{π}} {d_y}} \right)_{}^2} \right]^{1/2}} \end{split} \text{,} $
$ \frac{{\partial f}}{{\partial {\theta _a}}}=1 . $
复杂的海洋环境对相位测量的影响不可预估,实测相位误差较为复杂,同时,实际声速变化带来的折射效应也更加复杂,波束入射角精度对定位精度的影响更加难以评估,因此对超短基线声线跟踪的优化改进是有意义的。
为解决近似波束入射角引起的声线跟踪不准确问题,结合常梯度声线跟踪法,提出一种超短基线水声定位的波束入射角迭代修正方法。在改进方法中,近似波束入射角仅作为计算初值,通过在迭代计算过程中对波束入射角的渐次修正,实现准确的声线跟踪和定位计算。方法原理对于已知水深的水下目标,深度由压力传感器获得,通常认为其精度较高[32],以该深度为约束,在声速剖面、传播相位差、传播时间已知的情况下,则存在唯一的波束入射角满足换能器和目标间的传播条件,在确定此波束入射角后又可以通过声线跟踪获得较高精度距离观测值,进而提高目标的定位精度。
上述方法中的关键是如何反算波束入射角,由式(11)可以推算得到各层的传播时间为
$ \left\{ \begin{split}& {t_0} = {\rm{ln}}[{\rm{tan}}(\theta_1/2)/{\rm{tan}}(\theta_0/2)]/g_0 \\& {t_1} ={\rm{ln}}[{\rm{tan}}(\theta_2/2)/{\rm{tan}}(\theta_1/2)]/g_1\\ &\; \vdots \\& {t_n} = {\rm{ln}}[{\rm{tan}}(\theta_{n+1}/2)/{\rm{tan}}(\theta_n/2)]/g_n \end{split} \right.. $
结合式(6)将式(19)转换为关于波束入射角$\theta_0$的函数
$ \left\{ \begin{split}& {t_0} = {\rm{ln}}\left\{\frac{{\rm{tan}}[{\rm{arcsin}}(c_1\cdot {\rm{sin}}\;\theta_0/c_0)/2]}{{\rm{tan}(\theta_0/2)}}\right\}\\& {t_1} ={\rm{ln}}\left\{\frac{{\rm{tan}}[{\rm{arcsin}}(c_2\cdot {\rm{sin}}\;\theta_0/c_0)/2]}{{\rm{tan}[{\rm{arcsin}}(c_1\cdot {\rm{sin}}\;\theta_0/c_0)/2]}}\right\}\\ &\;\vdots \\& {t_n} = {\rm{ln}}\left\{\frac{{\rm{tan}}[{\rm{arcsin}}(c_{n+1}\cdot {\rm{sin}}\;\theta_0/c_0)/2]}{{\rm{tan}[{\rm{arcsin}}(c_n\cdot {\rm{sin}}\;\theta_0/c_0)/2]}}\right\}\end{split} \right.. $
各层内的声波传播时间之和应该等于时间延迟观测量,即
$ \begin{split} F({\theta _0})& = t = {t_0} + {t_1} + \cdots + {t_n} \\ & = {f_0}({\theta _0}) + {f_1}({\theta _0}) + \cdots + {f_n}({\theta _0}) \end{split} . $
式(21)是波束入射角$\theta_0$作为未知数的非线性方程,可以在一定范围搜索获得准确的波束入射角,但搜索法的计算效率较低。可采用牛顿迭代法[20]进行非线性方程解算,牛顿迭代法可以表示为
$ \theta_{h+1}=\theta_{h}-F\left(\theta_{h}\right) / F^{\prime}\left(\theta_{h}\right) \text{,} $
式中,迭代次数h = 0, 1, ···, r。对于式(22)的解算,可具体为
$ F\left(\theta_{h}\right)=\sum^r_{n\;=\;0} f\left(\theta_{h}\right)-t \text{,} $
$ F^{\prime}\left(\theta_{h}\right)=\sum^r_{n\;=\;0} f^{\prime}\left(\theta_{h}\right) . $
值得注意的是,牛顿迭代法需要一个较为准确的初值以保证迭代收敛,且需要对超越方程求导,计算较为复杂。
本文提出一种埃特金加速迭代法[33]来对这个超越方程进行解算获取准确的波束入射角,可避免求导并提高大型方程求根的效率。将式(21)转换为$\theta_0= \varphi(\theta_0) $的形式,根据超短基线系统观测值推算初始波束入射角$\theta_{0(0)} $,构造迭代函数:
$ \theta'_{0(m+1)}=\varphi[\theta_{0(m)}] \text{,} $
$ \theta''_{0(m+1)}=\varphi[\theta'_{0(m+1)}] \text{,} $
$ \theta_{0(m+1)}=\frac{[\theta'_{0(m+1)}]^2-\theta_{0(m)}\cdot \theta ''_{0(m+1)}}{2\theta'_{0(m+1)}-\theta_{0(m)}-\theta''_{0(m+1)}}\text{,} $
式中,迭代次数m = 0, 1, ···。结合式(21),对于式(25)的解算,可具体为
$ \begin{split} t_{0\left( {m + 1} \right)}' &= t - \left( {{t_1} + {t_2} + \cdots+{t_k}} \right) \\&= t - \left\{ {{f_1}\left[{{\theta _{0(m)}}} \right] + {f_2}\left[ {{\theta _{0(m)}}} \right] + \cdots + {f_k}\left[ {{\theta _{0(m)}}} \right]} \right\} \\ \end{split} \text{,} $
化简得
$ \theta _{0\left( {m + 1} \right)}' = 2\arctan \left\{ \begin{gathered} \tan \left[{{\text{arcsin}}\left( {{c_1} \cdot \sin {\theta _{0(m)}}/{c_0}} \right)/2} \right]/ \\ {{\rm{e}}^{\frac{{{g_0}\left\{ {t - \left[ {{f_1}\left( {{\theta _{0(m)}}} \right) + {f_2}\left( {{\theta _{0(m)}}} \right) + \cdots + {f_k}\left( {{\theta _{0(m)}}} \right)} \right]} \right\}}}{2}}} \\ \end{gathered} \right\} \text{,} $
式中,声速剖面分层数k = 0, 1, ···。
当在某一波束入射角下声线跟踪获得的声线传播时间与实测传播时间之差小于一定的阈值认为该波束入射角即为真实的波束入射角。
结合图4对超短基线的波束入射角迭代修正声线跟踪方法的计算流程说明如下:计算波束入射角:根据USBL观测时延、相位差及水深,结合式(2)、式(3)计算近似波束入射角,在近似入射角一定范围内搜索确定准确波束入射角θ0,或根据式(25)至式(29)采用解算法(埃特金加速迭代法)迭代计算波束入射角θ0;声线跟踪计算:由波束入射角θ0、系统观测值结合声速剖面,根据式(5)至式(12)计算修正后的距离ρi;计算目标坐标:由修正后的距离ρi代入式(1)至式(4)解算目标坐标(xt, yt, zt)。
超短基线测量综合多种观测数据共同解算水下目标的位置,其利用船体搭载的全球导航卫星系统(Global Navigation Satellite System, GNSS)接收机及船体姿态测量参数,以及仪器安装检校参数共同确定USBL换能器各观测历元的位置及姿态,结合压力传感器实时获得目标高精度水深,在此基础上利用换能器原始观测数据及声速剖面数据联合实时解算目标位置,结合USBL测量过程,其测量过程中必然会受到利用GNSS、姿态参数以及安装参数确定的超短基线换能器实时位置误差、换能器测量的相位测量误差、声速测量误差、仪器相关误差的影响。设计仿真实验,假设换能器处的声速测量误差为$ \Delta c=0.1 \;\mathrm{m} / \mathrm{s} $,相位差测量引起的测角误差为0.2°范围内的随机误差,参考高精度惯导的测姿精度,设姿态误差为∆θa = 0.06°,生成仿真数据。假定测区范围为3 000 m × 3 000 m,为了更好地获取不同波束入射角下的目标坐标,目标深度设置为1 500 m,在船体位置保持不变的情况下,模拟目标真实航行轨迹(图5),结合某实验声速剖面数据(图6),以常梯度声线跟踪法(搜索法)反算超短基线观测量即声线与xy轴的夹角、声线传播时间以及USBL换能器各历元初始波束入射角真值(5000历元)。结合仿真超短基线系统观测量,分别采用平均声速法、常梯度声线跟踪−近似波束入射角法、常梯度声线跟踪−搜索法、常梯度声线跟踪牛顿迭代法、常梯度声线跟踪埃特金加速迭代法进行水下目标的定位解算;仿真实验所用声速剖面如图6所示,将各个方法获得的水下目标坐标与仿真真值比较,获得各个方法目标坐标的标准差和各个方法计算所有历元目标坐标所需时间见表1;采用不同方法进行定位解算,统计波束入射角误差和定位误差,见图7图8;常梯度声线跟踪反算获取的各历元波束入射角真值如图9所示;常梯度声线跟踪−搜索法在搜索过程中不同波束入射角下计算得到的时间延迟误差如图10所示。
对实验结果的讨论分析如下:
解算获得波束入射角与仿真真值对比,由图7可以看出波束入射角迭代修正获得的波束入射角可减少各个测量误差带来的波束入射角误差,与真值相差极小;平均声速法和常梯度声线跟踪−近似波束入射角法声线跟踪其波束入射角均通过原始观测值直接获得,存在一定的误差,利用其进行定位解算,必然无法获得高精度的点位坐标。
定位精度分析,由表1图8可知,搜索法、牛顿迭代法、埃特金加速迭代法获得的结果几乎完全一致,说明3种方法均可有效消除声线折射效应对定位解算的影响;常梯度声线跟踪−近似波束入射角法也可获得较高精度的点位坐标,但结果较波束入射角迭代修正的常梯度声线跟踪差,说明波束入射角误差对声线跟踪的影响不可忽略;此外,平均声速法在不同声速条件下解算获得点位坐标标准差相差较大,说明声速的取值对超短基线定位解算精度影响较大,考虑到海水声速的时空变化,声速变化更加复杂,要想获得高精度点位坐标,声线跟踪的工作必不可少。
定位解算效率分析,由表1可知,平均声速法计算效率最高,结合其算法原理可知其数值计算简单,因此计算效率极高;常梯度声线跟踪−波束入射角搜索法理论严密但计算效率较低,对于实时定位的超短基线适用性较小,同时本文提出的常梯度声线跟踪−解算法(埃特金加速迭代法)计算效率最高,其在方程解算过程中加速迭代,且不用求导计算,公式简单易行,计算效率较牛顿迭代法明显提高,如表1所示,计算速度较牛顿迭代法提高3倍,较搜索法提高70倍之多,且对单历元的定位解算时间小于0.1 s,完全可应用于超短基线的实时解算。
波束入射角误差对定位解算影响的进一步分析,借助搜索法对不同历元的波束入射角分别在一定范围内搜索解算,根据时间延迟偏差与波束入射角关系可获得一条近似“√”形曲线如图10所示,波束入射角最优值位于曲线的最小值点,该曲线显示时间延迟偏差受波束入射角误差的影响较大,且随着波束入射角的增大,时间延迟偏差受波束入射角误差的影响逐渐增大,说明波束入射角越小波束入射角误差对定位误差的影响越小,但其误差影响不可忽略。
综上所述,波束入射角迭代优化的超短基线声线跟踪算法可较好地消除因海水介质不均匀引起的折射效应,传统搜索法虽可获得较高的目标解算精度,但计算量较大计算效率较低对超短基线的实时解算适用性不强;本文提出的解算法(埃特金加速迭代法)在保证计算精度的前提下,不用求导运算,计算方程简单,且具有加速迭代收敛的功能,极大地提高了计算效率;对声线跟踪具有普适性,可结合相关理论将其运用于同类水下导航计算中。
水下超短基线定位中的声线跟踪工作,需要已知精确的波束入射角,包含一定误差的波束入射角会造成声线跟踪结果不准确,将会带来一定的精度损失,本文提出的波束入射角迭代优化的常梯度声线跟踪算法(埃特金加速迭代法),在保证精度的前提下,较传统搜索法计算效率提高70倍,单历元解算时间较短,对超短基线实时高精度定位解算具有一定的适用性。
  • 国家自然科学基金(52101386,41930535);山东省高等学校青创人才引育计划−卫星定位导航研究创新团队项目;地理信息工程国家重点实验室、自然资源部测绘科学与地球空间信息技术重点实验室联合资助基金(2022−01−06)。
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2023年第45卷第9期
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doi: 10.12284/hyxb2023122
  • 接收时间:2022-09-02
  • 首发时间:2025-12-28
  • 出版时间:2023-09-30
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  • 收稿日期:2022-09-02
  • 修回日期:2023-04-19
基金
国家自然科学基金(52101386,41930535);山东省高等学校青创人才引育计划−卫星定位导航研究创新团队项目;地理信息工程国家重点实验室、自然资源部测绘科学与地球空间信息技术重点实验室联合资助基金(2022−01−06)。
作者信息
    1 山东电力工程咨询院有限公司,山东 济南 250013
    2 山东科技大学 测绘与空间信息学院,山东 青岛 266590
    3 浙江省水利河口研究院(浙江省海洋规划设计研究院),浙江 杭州 310020
    4 自然资源部海洋测绘重点实验室,山东 青岛 266590

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*卫进进(1997-),男,山西省运城市人,助理工程师,主要研究方向为海洋导航与定位。E-mail:
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2种不同金属材料的力学参数

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total species (%)

Genus
种数
Number of
species
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Percentage of total
species (%)
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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