Article(id=1322566845706645772, tenantId=1146029695717560320, journalId=1281212831689347082, issueId=1322566845215912204, articleNumber=null, orderNo=null, doi=10.14075/j.jgg.2025.03.072, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1741536000000, receivedDateStr=2025-03-10, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1793254108119, onlineDateStr=2026-10-29, pubDate=1771084800000, pubDateStr=2026-02-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793254108119, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793254108119, creator=13701087609, updateTime=1793254108119, updator=13701087609, issue=Issue{id=1322566845215912204, tenantId=1146029695717560320, journalId=1281212831689347082, year='2026', volume='46', issue='2', pageStart='139', pageEnd='261', issueExtLink='null', onlineDate='null', pubDate='1771084800000', pubDateStr='2026-02-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793254108003, creator='13701087609', updateTime=1793254108003, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=244, endPage=255, ext={EN=ArticleExt(id=1322566845899583757, articleId=1322566845706645772, tenantId=1146029695717560320, journalId=1281212831689347082, language=EN, title=Gravity Frequency Domain Continuation Methods and Error Factors, columnId=null, journalTitle=Journal of Geodesy and Geodynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

For the downward continuation method of gravity field, the frequency domain continuation method has different requirements for data noise and continuation distance, and there is no clear conclusion yet. This paper analyzes seven frequency domain downward continuation methods, including Milne method, Taylor series expansion method, integral iteration method, Tikhonov regularization method, CGNR method, iterative least squares method, and Landweber iterative method. The model was tested using simulation data and aviation measured data, and the results were compared and studied. The results show that the Milne method and the Taylor series expansion method can be used for continuation of point distances less than 14 times under noise-free conditions; the integral iteration method has better stability when continuation of point distances 1 to 20 times without noise, but is more sensitive to noise; the Tikhonov regularization method has significant advantages when it contains noise and is greater than 5 times of point distances, and can obtain higher accuracy; the CGNR method, iterative least squares method and Landweber iterative method have wide applicability, and can maintain high accuracy when continuation of point distances 1 to 20 times under different noise conditions. Among them, the noise resistance of the Landweber iterative method is the most outstanding, and the latter four methods show certain advantages in actual data experiments, and can obtain stable downtime results.

, authors=Huaikui GUAN1, 2, Yun XIAO2, 3, *, Feilong REN4, Han WANG1, 2, Weixuan SUN1, 2, authorsList=Huaikui GUAN, Yun XIAO, Feilong REN, Han WANG, Weixuan SUN, authorCompany=null, correspAuthors=Yun XIAO, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., 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, fund=null), CN=ArticleExt(id=1322566850836279598, articleId=1322566845706645772, tenantId=1146029695717560320, journalId=1281212831689347082, language=CN, title=重力场频率域延拓方法分析及误差因素研究, columnId=1281909276545356011, journalTitle=大地测量与地球动力学, columnName=大地测量学, runingTitle=null, highlight=null, articleAbstract=

基于重力场各向下延拓方法采用频率域延拓对数据噪声和延拓距离有不同的要求, 且尚未有较明确的结论, 分析了Milne法、泰勒级数展开法、积分迭代法、Tikhonov正则化法、CGNR法、迭代最小二乘法、Landweber迭代法共7种的频率域向下延拓方法, 利用仿真数据和航空实测数据进行模型检验, 并对结果进行对比研究。结果表明, Milne法及泰勒级数展开法可用于无噪声条件下小于14倍点距的延拓; 积分迭代法在无噪声1~20倍点距延拓时稳定性较好, 但对噪声较为敏感; Tikhonov正则化法在含噪声且大于5倍点距的情况下优势显著, 可获得较高精度的下延结果; CGNR法、迭代最小二乘法和Landweber迭代法具有较广的适用性, 在不同噪声条件下进行1~20倍点距延拓时均能保持较高精度, 其中Landweber迭代法的抗噪性能最为突出, 且后4种方法在实测数据实验中表现出一定的优势, 能得到稳定的下延结果。

, authors=关怀魁1, 2, 肖云2, 3, *, 任飞龙4, 王翰1, 2, 孙玮萱1, 2, authorsList=关怀魁, 肖云, 任飞龙, 王翰, 孙玮萱, authorCompany=null, correspAuthors=肖云, authorNote=

关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

, correspAuthorsNote=
肖云, 博士, 正研级高级工程师, 主要研究方向为重力测量与导航, E-mail:
, copyrightStatement=版权所有,未经授权,不得转载。, copyrightOwner=大地测量与地球动力学编辑部, extLink=null, articleAbsUrl=null, sourceXml=wZ9MrWaeAZ2uZgWVx32Nng==, magXml=QHGuLvycWFQcn3NLYkCiyw==, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=MJpbZqOkbe8xO7Z2ZdLKYA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=ukrkEdpL1b9CPA9o6lVotg==, mapNumber=null, fund=null)}, authors=[Author(id=1322566851914215741, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=2177585853@qq.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1322566852006490432, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, authorId=1322566851914215741, language=EN, stringName=Huaikui GUAN, firstName=Huaikui, middleName=null, lastName=GUAN, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, address=1 School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
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关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

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关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

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Parameter settings of the point quality source

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点质量源序号经度/(°)纬度/(°)埋深/km质量/kg
1151.04024.0400.7561.850×1013
2151.05024.1050.808-1.800×1013
3151.07524.0750.7671.950×1013
4151.10024.0380.8081.800×1013
5151.10024.1190.7561.850×1013
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点质量源参数设置

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点质量源序号经度/(°)纬度/(°)埋深/km质量/kg
1151.04024.0400.7561.850×1013
2151.05024.1050.808-1.800×1013
3151.07524.0750.7671.950×1013
4151.10024.0380.8081.800×1013
5151.10024.1190.7561.850×1013
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Comparison of 10 times the point distance error of noise-free downward continuation

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法0.338-1.9580.2000.1271.133
泰勒级数展开法0.228-1.3270.1780.1260.479
积分迭代法0.228-1.3270.1780.1260.846
Tikhonov正则化法0.187-1.3650.2110.1520.860
CGNR法0.069-0.7190.1590.1220.982
迭代最小二乘法0.160-0.7090.1690.1260.913
Landweber迭代法0.185-0.6930.1580.12218.245
), ArticleFig(id=1322566870272684431, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=CN, label=表2, caption=

无噪声向下延拓10倍点距误差比较

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法0.338-1.9580.2000.1271.133
泰勒级数展开法0.228-1.3270.1780.1260.479
积分迭代法0.228-1.3270.1780.1260.846
Tikhonov正则化法0.187-1.3650.2110.1520.860
CGNR法0.069-0.7190.1590.1220.982
迭代最小二乘法0.160-0.7090.1690.1260.913
Landweber迭代法0.185-0.6930.1580.12218.245
), ArticleFig(id=1322566872244007313, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=EN, label=Tab. 3, caption=

Comparison of 20 times the point distance error of noise-free downward continuation

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法4.177-5.3360.8410.4661.138
泰勒级数展开法5.318-6.7540.9940.5600.480
积分迭代法1.714-4.4290.5800.3490.928
Tikhonov正则化法1.647-2.6830.5360.3230.837
CGNR法1.178-2.1920.5120.3511.157
迭代最小二乘法1.328-2.2620.5090.3501.546
Landweber迭代法1.329-2.2510.5000.33338.082
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无噪声向下延拓20倍点距误差比较

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法4.177-5.3360.8410.4661.138
泰勒级数展开法5.318-6.7540.9940.5600.480
积分迭代法1.714-4.4290.5800.3490.928
Tikhonov正则化法1.647-2.6830.5360.3230.837
CGNR法1.178-2.1920.5120.3511.157
迭代最小二乘法1.328-2.2620.5090.3501.546
Landweber迭代法1.329-2.2510.5000.33338.082
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Comparison of 10 times point distance error of 5% noise downward continuation

, figureFileSmall=null, figureFileBig=null, tableContent=
延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法15.787-14.7523.5292.8151.881
泰勒级数展开法7.506-7.9561.7781.4190.482
积分迭代法4.994-5.4180.9290.6650.825
Tikhonov正则化法0.701-1.4820.2920.2250.844
CGNR法1.227-1.8440.3430.2730.939
迭代最小二乘法1.268-1.8190.3420.2720.914
Landweber迭代法0.305-0.6860.1730.13314.071
), ArticleFig(id=1322566873061896596, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=CN, label=表4, caption=

5%噪声向下延拓10倍点距误差比较

, figureFileSmall=null, figureFileBig=null, tableContent=
延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法15.787-14.7523.5292.8151.881
泰勒级数展开法7.506-7.9561.7781.4190.482
积分迭代法4.994-5.4180.9290.6650.825
Tikhonov正则化法0.701-1.4820.2920.2250.844
CGNR法1.227-1.8440.3430.2730.939
迭代最小二乘法1.268-1.8190.3420.2720.914
Landweber迭代法0.305-0.6860.1730.13314.071
), ArticleFig(id=1322566873145782677, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=EN, label=Tab. 5, caption=

Comparison of 20 times point distance error of 5% noise downward continuation

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法31.575-29.5527.0985.6621.935
泰勒级数展开法10.497-12.5022.0351.5830.510
积分迭代法10.562-12.8841.9161.4310.842
Tikhonov正则化法1.717-2.9870.5790.3680.855
CGNR法1.657-3.3630.6130.4591.136
迭代最小二乘法1.840-3.3110.6060.4461.482
Landweber迭代法1.306-2.2870.5260.36234.706
), ArticleFig(id=1322566873485521302, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=CN, label=表5, caption=

5%噪声向下延拓20倍点距误差比较

, figureFileSmall=null, figureFileBig=null, tableContent=
延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法31.575-29.5527.0985.6621.935
泰勒级数展开法10.497-12.5022.0351.5830.510
积分迭代法10.562-12.8841.9161.4310.842
Tikhonov正则化法1.717-2.9870.5790.3680.855
CGNR法1.657-3.3630.6130.4591.136
迭代最小二乘法1.840-3.3110.6060.4461.482
Landweber迭代法1.306-2.2870.5260.36234.706
), ArticleFig(id=1322566873577795991, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=EN, label=Tab. 6, caption=

Comparison of downward continuation errors of each method

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延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法71.335-75.63417.25113.7391.002
泰勒级数展开法16.437-17.9693.8773.0890.596
积分迭代法10.139-8.3461.9881.5480.722
Tikhonov正则化法6.033-6.5631.2090.8301.137
CGNR法6.175-7.7041.1110.8410.822
迭代最小二乘法6.326-7.0810.9630.7400.908
Landweber迭代法4.997-6.7010.7570.53120.560
), ArticleFig(id=1322566873670070680, tenantId=1146029695717560320, journalId=1281212831689347082, articleId=1322566845706645772, language=CN, label=表6, caption=

各方法向下延拓误差比较

, figureFileSmall=null, figureFileBig=null, tableContent=
延拓方法残差最大值/mGal残差最小值/mGalRMSE/mGalMAE/mGal计算时间/s
Milne法71.335-75.63417.25113.7391.002
泰勒级数展开法16.437-17.9693.8773.0890.596
积分迭代法10.139-8.3461.9881.5480.722
Tikhonov正则化法6.033-6.5631.2090.8301.137
CGNR法6.175-7.7041.1110.8410.822
迭代最小二乘法6.326-7.0810.9630.7400.908
Landweber迭代法4.997-6.7010.7570.53120.560
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重力场频率域延拓方法分析及误差因素研究
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关怀魁 1, 2 , 肖云 2, 3, * , 任飞龙 4 , 王翰 1, 2 , 孙玮萱 1, 2
大地测量与地球动力学 | 大地测量学 2026,46(2): 244-255
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大地测量与地球动力学 |大地测量学 2026 , 46 (2) : 244 -255
重力场频率域延拓方法分析及误差因素研究
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关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

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关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

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关怀魁1, 2 , 肖云2, 3, * , 任飞龙4, 王翰1, 2, 孙玮萱1, 2
作者信息
  • 1 长安大学地质工程与测绘学院, 西安, 710054
  • 2 地理信息工程国家重点实验室, 西安, 710054
  • 3 西安测绘研究所, 西安, 710054
  • 4 西安航天天绘数据技术有限公司, 西安, 710100
通讯作者:
肖云, 博士, 正研级高级工程师, 主要研究方向为重力测量与导航, E-mail:
作者简介:

关怀魁, 硕士生, 主要研究方向为水下重力延拓, E-mail:

Gravity Frequency Domain Continuation Methods and Error Factors
Huaikui GUAN1, 2 , Yun XIAO2, 3, * , Feilong REN4, Han WANG1, 2, Weixuan SUN1, 2
Affiliations
  • 1 School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, China
  • 2 State Key Laboratory of Geo-Information Engineering, Xi'an 710054, China
  • 3 Xi'an Institute of Surveying and Mapping, Xi'an 710054, China
  • 4 Xi'an Aerospace Remote Sensing Data Technology Corporation, Xi'an 710100, China
出版时间: 2026-02-15 doi: 10.14075/j.jgg.2025.03.072
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基于重力场各向下延拓方法采用频率域延拓对数据噪声和延拓距离有不同的要求, 且尚未有较明确的结论, 分析了Milne法、泰勒级数展开法、积分迭代法、Tikhonov正则化法、CGNR法、迭代最小二乘法、Landweber迭代法共7种的频率域向下延拓方法, 利用仿真数据和航空实测数据进行模型检验, 并对结果进行对比研究。结果表明, Milne法及泰勒级数展开法可用于无噪声条件下小于14倍点距的延拓; 积分迭代法在无噪声1~20倍点距延拓时稳定性较好, 但对噪声较为敏感; Tikhonov正则化法在含噪声且大于5倍点距的情况下优势显著, 可获得较高精度的下延结果; CGNR法、迭代最小二乘法和Landweber迭代法具有较广的适用性, 在不同噪声条件下进行1~20倍点距延拓时均能保持较高精度, 其中Landweber迭代法的抗噪性能最为突出, 且后4种方法在实测数据实验中表现出一定的优势, 能得到稳定的下延结果。

重力场  /  向下延拓  /  频率域  /  噪声敏感性  /  延拓距离

For the downward continuation method of gravity field, the frequency domain continuation method has different requirements for data noise and continuation distance, and there is no clear conclusion yet. This paper analyzes seven frequency domain downward continuation methods, including Milne method, Taylor series expansion method, integral iteration method, Tikhonov regularization method, CGNR method, iterative least squares method, and Landweber iterative method. The model was tested using simulation data and aviation measured data, and the results were compared and studied. The results show that the Milne method and the Taylor series expansion method can be used for continuation of point distances less than 14 times under noise-free conditions; the integral iteration method has better stability when continuation of point distances 1 to 20 times without noise, but is more sensitive to noise; the Tikhonov regularization method has significant advantages when it contains noise and is greater than 5 times of point distances, and can obtain higher accuracy; the CGNR method, iterative least squares method and Landweber iterative method have wide applicability, and can maintain high accuracy when continuation of point distances 1 to 20 times under different noise conditions. Among them, the noise resistance of the Landweber iterative method is the most outstanding, and the latter four methods show certain advantages in actual data experiments, and can obtain stable downtime results.

gravity field  /  downward continuation  /  frequency domain  /  noise sensitivity  /  continuation distance
关怀魁, 肖云, 任飞龙, 王翰, 孙玮萱. 重力场频率域延拓方法分析及误差因素研究. 大地测量与地球动力学, 2026 , 46 (2) : 244 -255 . DOI: 10.14075/j.jgg.2025.03.072
Huaikui GUAN, Yun XIAO, Feilong REN, Han WANG, Weixuan SUN. Gravity Frequency Domain Continuation Methods and Error Factors[J]. Journal of Geodesy and Geodynamics, 2026 , 46 (2) : 244 -255 . DOI: 10.14075/j.jgg.2025.03.072
向下延拓是不适定问题,具有下延不稳定、受噪声影响大、下延深度小等问题。针对向下延拓面临的问题,众多研究者给出许多不同的解决方法,可以简单归纳为两大类:1)第1类是空间域延拓,具有更加精确和灵活的特点,但是空间域具有效率低的局限性[1-4];2)第2类是频率域延拓,向上延拓在频率域可得到稳定结果,但对于直接向下延拓,频率域向下延拓算子是典型的高通滤波器,结果受高频影响较大,导致结果不稳定[5],只能实现近距离的延拓。为提高延拓效率,增大延拓距离,改善向下延拓的精度,众多研究者对向下延拓方法在频率域进行了研究[6-13],并取得了较好的结果,但各种延拓方法采用频率域延拓对于数据噪声和延拓距离有不同的要求,目前尚无较明确的结论。
基于上述问题,本文分析了Milne法、泰勒级数展开法、积分迭代法、Tikhonov正则化法、迭代最小二乘法、CGNR法及Landweber迭代法共7种频率域重力场向下延拓方法,并进行仿真实验及航空实测重力数据实验,重点对下延深度、延拓精度、计算效率、抗噪能力等相互关系进行对比研究,得到一些有益的结论。
在空间域,z轴方向竖直向下,重力数值向上延拓可表示为如下褶积型线性积分[14]:
$\Delta \boldsymbol{g}(x, y, 0)=\frac{h}{2 \pi} \int\limits_{-\infty}^{+\infty} \int \limits_{-\infty}^{+\infty} \frac{\Delta \boldsymbol{g}\left(x^{\prime}, y^{\prime}, h\right)}{l^3} \mathrm{~d} x^{\prime} \mathrm{d} y^{\prime}$
式中,$l=\sqrt{\left(x-x^{\prime}\right)^2+\left(y-y^{\prime}\right)^2+h^2}, h$为延拓距离;$\Delta \boldsymbol{g}\left(x^{\prime}, y^{\prime}, h\right)$为下层平面的重力数值;$\Delta \boldsymbol{g}(x, y, 0)$为上层平面的重力数值。式(1)可表示为如下二维卷积形式:
$\Delta \boldsymbol{g}(x, y, 0)=\Delta \boldsymbol{g}(x, y, h) * \varphi(x, y)$
式中,*表示二维卷积;$\varphi(x, y)=\frac{1}{2 \pi}·\frac{h}{\left(x^2+y^2+h^2\right)^{\frac{3}{2}}}$为积分核函数。式(2)在频率域可表达为:
$U_0(u, v)=U_h(u, v) \varphi(u, v)$
式中,$U_0(u, v) 、U_h(u, v)$分别为$\Delta \boldsymbol{g}(x, y, 0)$与$\Delta \boldsymbol{g}(x, y, h)$的二维傅里叶变换;$\varphi(u, v)= \mathrm{e}^{-2 \pi h \sqrt{u^2+v^2}}$为$\varphi(x, y)$的傅里叶变换;$u 、v$分别为$x 、y$方向的频率。若空间域已知$\Delta \boldsymbol{g}(x, y, 0)$求$\Delta \boldsymbol{g}(x, y, h)$,或频率域已知$U_0(u, v)$求$U_h(u , v)$,即为向下延拓。
向下延拓问题能够转化为常微分方程初值问题,进而通过线性多步法解算[15],本文以Milne法为例,进行重力场的延拓求解。式(2)中下层重力场$\Delta \boldsymbol{g}(x, y, h)$可通过Milne法用$\Delta \boldsymbol{g}(x, y, 0)$表示,其频率域表达式见参考文献[12]。
式(2)中下层重力场$\Delta \boldsymbol{g}(x, y, h)$可通过泰勒级数展开用上层重力场$\Delta \boldsymbol{g}(x, y, 0)$表示[16]:
$\begin{gathered}\Delta \boldsymbol{g}(x, y, h)=\Delta \boldsymbol{g}(x, y, 0)+ \\h \frac{\partial \Delta \boldsymbol{g}(x, y, 0)}{\partial z}+\frac{h^2}{2!} \frac{\partial^2 \Delta \boldsymbol{g}(x, y, 0)}{\partial z^2}+\cdots+ \\\frac{h^m}{m!} \frac{\partial^m \Delta \boldsymbol{g}(x, y, 0)}{\partial z^m}\end{gathered}$
参考文献[16]将该方法在频率域用于向下延拓。
在频率域,积分迭代法是一种逐步迭代逼近Uh(u, v)的方法,其表达式[9]为:
$\begin{gathered}U_n(u, v)=U_{n-1}(u, v)+\left[U_0(u, v)-\right. \\\left.U_{n-1}(u, v) \varphi(u, v)\right], n=1, 2, 3 \cdots\end{gathered}$
式中,Un(u, v)为第n次迭代结果;Un-1(u, v)φ(u, v) 为第n-1次迭代值向上延拓到观测面的结果;[·]中的表达式为每次迭代的校正值。
式(2)可表示为算子表达式:$\Delta \boldsymbol{g}(x, y, 0)=Κ\Delta \boldsymbol{g}(x, y, h)$,式中Κ为第1类Fredholm积分算子。Tikhonov正则化法被广泛应用于解决不适定问题,其基本思想为求解一个极小化的正则化泛函[17]:
$\begin{gathered}\min \left\{\|K \Delta \boldsymbol{g}(x, y, h)-\Delta \boldsymbol{g}(x, y, 0)\|_2^2+\right. \\\alpha\|\Delta \boldsymbol{g}(x, y, h)\|_2^2\end{gathered}$
对式(6)进行求解,即可得其频率域解Uh(u, v)。
CGNR法是一种特定的共轭梯度方法。将式(2)进行离散化,并变成矩阵形式$\boldsymbol{A X}=\boldsymbol{B}$,将求解关于矩阵$\boldsymbol{A X}=\boldsymbol{B}$重力场下延的不稳定问题转化为共轭梯度法求解$\boldsymbol{A}^{\mathrm{T}} \boldsymbol{A X}=\boldsymbol{A}^{\mathrm{T}} \boldsymbol{B}$的问题,即CGNR法。参考文献[13]实现了CGNR法在频率域的向下延拓。
将式(2)进行离散化处理,并变成矩阵形式$\boldsymbol{A X}=\boldsymbol{B}$,其中已知重力场与待求重力场重新排列成列向量形式,即B与X,A可以看成某种意义上的卷积算子。
向下延拓问题是不适定问题,将延拓问题转化成目标函数为$\frac{1}{2}\|\boldsymbol{A} \boldsymbol{X}-\boldsymbol{B}\|_2$的最小二乘问题,结合梯度下降法,在其负梯度方向引入步长λ进行迭代求解[11]。
Landweber迭代法空间域迭代通式为[10]:
$\begin{gathered}\Delta \boldsymbol{g}_n(x, y, h)=\Delta \boldsymbol{g}_{n-1}(x, y, h)+ \\\alpha \boldsymbol{K}^{\mathrm{T}}\left[\Delta \boldsymbol{g}(x, y, 0)-\boldsymbol{K} \Delta \boldsymbol{g}_{n-1}(x, y, h)\right], \\n=2, 3 \cdots\end{gathered}$
令$\Delta \boldsymbol{g}_1(x, y, h)=0$,其中α是满足$0<\alpha \leqslant \frac{1}{\|K\|^2}$的正则参数,也可认为是Landweber迭代法的迭代步长,其频率域表达式由参考文献[10]给出。
采用模型数据进行仿真实验,具体见参考文献[13]。以点质量源组合作为重力场场源模型,假设151°~151.15°E、24°~24.15°N为实验区域,表 1为实验区域内5个点质量源的参数设置。将实验区域表面视为地球表面,以50 m为垂向间隔,在距离地表1~2 km的高度范围内均匀布设21个水平高度面,分别模拟各高度面处的重力场格网数据,矩形格网参数设置为线数M=301,每线点数N=301,点距、线距约为50 m。将2 km处的重力场格网数据作为已知观测位场,其余格网数据分别作为不同的下层位场,即模拟向下延拓1~20倍点距的结果,与下层位场重力数据比较,验证向下延拓效果。本文通过无噪声及1%、3%、5%不同高斯白噪声条件下的实验,分析各方法向下延拓1~20倍点距的误差变化规律。为进一步评估各方法的性能,重点对比了无噪声及5%噪声条件下向下延拓10倍及20倍点距的结果等值线、残差分布及误差统计特征。
采用上述各种延拓方法,对2 km理论重力场数据分别进行1~20倍点距的向下延拓。为避免边界效应对延拓结果产生较大影响,实验时将2 km理论重力场数据进行扩边,扩边后线数M=512,点数N=512。实验采用均方根误差(RMSE)和平均绝对误差(MAE)来衡量各方法的延拓精度。图 1为各方法在无噪声条件下RMSE及MAE随点距变化曲线分布,随着向下延拓距离的增加,各方法的延拓精度均呈现下降趋势。当延拓距离小于14倍点距时,各方法均有较好的延拓精度;当延拓距离大于14倍点距时,泰勒级数展开法及Milne法的误差值增幅较大,其余5种方法仍保持较好的延拓精度。
表 2为各向下延拓方法在未加入噪声条件下,下延10倍点距误差对比。可以看出,各方法RMSE和MAE均较小,其中Landweber迭代法收敛速度较慢,需较长的计算时间。图 2为模拟1 km、1.5 km和2 km三个高度面上的理论重力场等值线分布,图 3为各方法在无噪声条件下,下延10倍点距的等值线分布。与图 2中1.5 km理论重力场相比,各方法等值线分布均相似。图 4为无噪声条件下各方法下延10倍点距结果与理论数值的残差分布,各延拓结果偏差大范围在0~0.1 mGal之间,准确性都较高,各方法峰值处都有轻微的绝对值偏小现象。尽管进行了数据扩边处理,但并不能完全避免边界效应,各方法均存在边界问题,其中CGNR法、迭代最小二乘法、Landweber迭代法边界误差明显小于其他方法。结合表 2可知,各延拓方法延拓精度均较好。
表 3为各方法在未加入噪声条件下,下延20倍点距误差对比。对比表 2可以看出,各延拓方法RMSE与MAE均增大,各方法的延拓精度均降低,其中泰勒级数展开法、Milne法延拓精度较差,积分迭代法、Tikhonov正则化法、CGNR法、迭代最小二乘法、Landweber迭代法仍有较高的延拓精度。
图 5分别为各方法在无噪声条件下,下延20倍点距的等值线分布,图 6为无噪声条件下各方法下延20倍点距结果与理论数值的差值分布。整体来看,各方法在大部分区域都能较好地逼近1 km理论重力场数值,偏差大部分在0~0.4 mGal之间。其中,泰勒级数展开法、Milne法有较为严重的峰值绝对值偏小现象。对比图 4可知,各方法的边界误差均增大,CGNR法、迭代最小二乘法、Landweber迭代法边界误差相对较小。
为更好地模拟实际数据情况,向2 km无误差模型数据中分别加入1%、3%、5%的高斯白噪声,对其用各种方法进行1~20倍点距的延拓,并与理论重力场对比,分析各方法延拓精度与抗噪能力。实验时将2 km理论噪声重力场数据进行扩边,扩边后线数、点数均为512。
图 7为各方法在不同噪声条件下RMSE与MAE随点距变化曲线对比,图 8为同噪声条件下各方法RMSE与MAE随点距变化曲线对比。由图 7可知,下延到相同点距时,随着噪声的增加,各方法RMSE及MAE均增大,各方法的精度均降低。在噪声影响下,Tikhonov正则化法、CGNR法、迭代最小二乘法及Landweber迭代法在某些情况下会表现出下延最佳点距现象。由图 8可知,在噪声的影响下,Milne法相较于其他方法误差增幅最大,下延结果精度差;泰勒级数展开法、积分迭代法误差较大;Tikhonov正则化法在小距离延拓时,精度不如CGNR法、迭代最小二乘法及Landweber迭代法,但在大于5倍点距延拓时,4种方法延拓结果无显著差异,抗噪能力较强;CGNR法、迭代最小二乘法结果精度相似性高;在各噪声实验中,Landweber迭代法误差值均最小,延拓结果精度最高, 结合图 7可知,随着噪声强度的增加,误差无显著变化,展现出卓越的抗噪性能和算法稳健性。
表 4为各方法在5%噪声条件下,下延10倍点距误差对比。可以看出,Milne法、泰勒级数展开法、积分迭代法的延拓精度较低,Tikhonov正则化、CGNR法、迭代最小二乘法、Landweber迭代法有较好的延拓精度。其中,Landweber迭代法误差最小,且与无噪声下延10倍点距误差无显著差异(表 2),说明该方法精度最高,抗噪能力最强,但收敛速度较慢,耗时较长。
图 9为5%高斯白噪声情况下2 km理论重力场等值线分布,图 10为各方法在5%噪声条件下, 下延10倍点距的等值线分布,图 11为图 10对应的差值分布。可以看出,Milne法与泰勒级数展开法的等值线较为粗糙,受噪声影响大,噪声分布不集中,抗噪能力差;积分迭代法等值线图平滑性稍差,且其峰值部分与理论重力场相似性较差,有明显的绝对值偏小现象;Tikhonov正则化法、CGNR法、迭代最小二乘法的等值线图较为平滑,误差主要集中在边缘部分,延拓精度较高;Landweber迭代法等值线图最平滑,几乎无噪声点,与理论等值线图拟合程度最高。
表 5为各方法在5%噪声条件下,下延20倍点距误差对比。可以看出,Milne法的延拓精度下降程度最为明显,且精度最低;积分迭代法、泰勒级数展开法的延拓精度较低。在噪声的影响下增加延拓深度,Tikhonov正则化法、CGNR法、迭代最小二乘法、Landweber迭代法仍保持着较好的延拓精度,对噪声有较好的抑制作用,其中Landweber迭代法误差最小,精度最高,且与表 3无显著差异,抗噪能力强。
图 12为各方法在5%噪声条件下,下延20倍点距的等值线分布,图 13为各方法下延结果与理论数值的残差分布。可以看出,Milne法计算结果误差较大,对噪声较为敏感,表现为等值线中噪声点分布散乱,仅能大致反映轮廓特征。泰勒级数展开法与积分迭代法的等值线较为粗糙,且有明显的峰值等值线缺失现象;迭代最小二乘法、CGNR法的等值线较为平滑,对噪声的抑制作用较好,与理论数据的差值较小;Tikhonov正则化法与Landweber迭代法等值线最为平滑,几乎无噪声点。
本文采用墨西哥湾某一方形区域的航空重力数据进行实测数据实验分析,具体范围为90.5°~92.5°W、27°~29°N,研究区域内重力数据信息较为丰富。观测航线由横测线与纵测线组成,观测阶段飞机飞行高度平稳,满足延拓要求,平均飞行高度约为11 111 m。经预处理得到平均飞行高度面上的重力异常数据(图 14(a)),数据格网大小为400×400,格网间距约为550 m。为创建用于验证各方法向下延拓效果的上层数据,将下层重力异常数据向上延拓11 000 m(20倍点距)。向上延拓具有平滑作用,为使上层数据具有更高的真实性,在上层数据中加入5%高斯白噪声,图 14(c)为加入噪声后的重力数据等值线分布。
为缓解边界效应对延拓结果的影响,对实验数据实施了扩边操作,扩边后的格网大小为512×512。图 15为各方法下延拓等值线分布,结合表 6可以看出,几种延拓方法中Milne法的结果受噪声影响最明显,噪声点分布杂乱,延拓结果差;泰勒级数展开法与积分迭代法的效率较高,但其抗噪能力较差,整体延拓结果不够平滑;迭代最小二乘法、Tikhonov正则化法、CGNR法的下延结果较为平滑,Landweber迭代法等值线图最平滑,精度最高,但向下延拓收敛速度较慢,所需计算时间较长, 以上4种方法结果与原始数据差值较小(图 16),能更好地还原下层真实重力异常。
本文针对重力场各向下延拓方法采用频率域延拓对数据噪声和延拓距离有不同要求,且尚未有较明确的结论,分析了Milne法、泰勒级数展开法、积分迭代法、Tikhonov正则化法、CGNR法、迭代最小二乘法、Landweber迭代法7种重力场频率域向下延拓方法,并进行仿真实验及航空实测数据实验,对比研究各延拓方法的下延深度、延拓精度、计算效率、抗噪能力等相互关系。
1) 相较于空间域延拓,7种向下延拓方法在频率域都具有较高的计算效率。实验中,除Landweber迭代法外,其他几种方法在计算效率上无显著差异,均能在2 s内完成任务。
2) 在无噪声的条件下,随着下延距离的增加,各延拓方法的精度均降低。当向下延拓距离小于14倍点距时,各方法均有较好的延拓精度;当延拓深度大于14倍点距时,Milne法、泰勒级数展开法误差值大幅增加,精度开始明显低于其他方法;当向下延拓20倍点距时,Milne法及泰勒级数展开法在数据峰值处呈现较为严重的幅值衰减现象,其余方法能更好地反映延拓面的实际情况。
3) 在含噪声实验中,随着噪声的增大,各延拓方法的精度均降低。在同噪声条件下,Milne法、泰勒级数展开法及积分迭代法的精度低于其他方法,Landweber迭代法、迭代最小二乘法、CGNR法、Tikhonov正则化法的精度较高;随着下延点距增加到20倍,4种方法仍保持着较好的延拓精度,稳健性较高。其中,Landweber迭代法在不同噪声实验中的误差无显著差异,抗噪能力最强,能获得更稳定平滑的下延结果。
4) Milne法、泰勒级数展开法对噪声敏感,可用于无噪声小距离延拓。在其他实验条件下,结果精度小于其他方法,且稳健性较差,随着噪声的增加及距离的增大,误差增幅较大,精度下降较快。
5) 积分迭代法适用于无噪声重力数据延拓。在无噪声条件下,积分迭代法向下延拓20倍点距仍可保持较好的延拓精度;在噪声实验中,其延拓精度相较于Landweber迭代法、迭代最小二乘法、CGNR法、Tikhonov正则化法变低,且随着距离的增加,差距越大。
6) 在含噪声大于5倍点距延拓时,Tikhonov正则化法更能体现其优势;在无噪声实验及含噪声小距离实验中,其精度相较于Landweber迭代法、迭代最小二乘法、CGNR法稍差;在含噪声大于5倍点距延拓实验中,正则化参数选择合适时,其结果与以上3种方法无显著差异。
7) 在重力数据延拓时,可优先选择Landweber迭代法、迭代最小二乘法、CGNR法。在无噪声实验中,3种方法边界误差较小,延拓结果精度无显著差异,且高于其他几种方法;在噪声实验中,3种方法均能获得较好的下延结果,其中Landeweber迭代法抗噪能力最优,结果精度最高,但其收敛速度较慢,计算时间较长。
8) 在实测数据中,迭代最小二乘法、CGNR法及Tikhonov正则化法能较好地抑制噪声,得到较为平滑的结果,精度较高;Landweber迭代法抗噪能力最强,精度最高。其中,Landweber迭代法收敛速度较慢,但其在频率域中仅耗时20.56 s。因此,使用这4种方法在频率域处理实测数据时,精度较高、速度较快,对噪声具有较好的抑制作用,具有一定的优越性。
结合仿真实验及航空实测数据实验,Milne法及泰勒级数展开法可用于无噪声条件下小于14倍点距的延拓;积分迭代法对噪声敏感,但在无噪声1~20倍点距延拓时稳定性较好;Tikhonov正则化法在含噪声且大于5倍点距的情况下优势显著,可获得较高精度的下延结果;CGNR法、迭代最小二乘法、Landweber迭代法适用范围最广,在不同噪声条件下向下延拓1~20倍点距,均能得到较高精度的结果,其中Landweber迭代法抗噪能力最优,且后4种方法在实测数据实验中表现出一定的优势,能快速得到稳定的下延结果。
  • 国家重点研发计划(2021YFB3900604)
  • 长安大学研究生科研创新实践项目(300103725040)
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2026年第46卷第2期
39
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doi: 10.14075/j.jgg.2025.03.072
  • 接收时间:2025-03-10
  • 首发时间:2026-10-29
  • 出版时间:2026-02-15
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  • 收稿日期:2025-03-10
基金
国家重点研发计划(2021YFB3900604)
长安大学研究生科研创新实践项目(300103725040)
作者信息
    1 长安大学地质工程与测绘学院, 西安, 710054
    2 地理信息工程国家重点实验室, 西安, 710054
    3 西安测绘研究所, 西安, 710054
    4 西安航天天绘数据技术有限公司, 西安, 710100

通讯作者:

肖云, 博士, 正研级高级工程师, 主要研究方向为重力测量与导航, E-mail:
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2种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
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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