Point displacements during classical measurements – a practical approach to pseudo epochs between measurements

R. Duchnowski, P. Wyszkowska
{"title":"Point displacements during classical measurements – a practical approach to pseudo epochs between measurements","authors":"R. Duchnowski, P. Wyszkowska","doi":"10.4995/jisdm2022.2022.13678","DOIUrl":null,"url":null,"abstract":"Various measurement techniques and data processing are applied to determine point displacements and deformation of geodetic networks or buildings. Considering classical measurements and analysis of the network deformation, we should realize that the measurements are not “immediate.” The question arises: what happens if a point (or some points) displaces between particular measurements within one epoch. In such a case, the observation set would consist of the observations before and after point displacement, and such hypothetical observation groups can be regarded as related to two (or more) pseudo epochs. The paper's main objective is to examine some estimation methods that would probably deal with such a problem, namely Msplit estimation (in two variants, the squared and the absolute Msplit estimation) and chosen robust methods, namely Huber’s method (example M-estimation) and the Hodges-Lehmann weighted estimation (basic R-estimation). The first approach can provide two (or more) variants of the network point coordinates (here, before and after point movements), providing information about two (or more) states of the network during measurements. In contrast, the robust methods can only decrease the influence of the outliers on the computed network point coordinates. Thus, estimation results would concern only one network state in such a case. The presented empirical analyses show that the better and more realistic results are obtained by applying Msplit estimation. Huber’s method can also provide acceptable results (describing the network state at the epoch beginning) only if the number of observations conducted after the point displacements is not too high.","PeriodicalId":404487,"journal":{"name":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","volume":"100 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 5th Joint International Symposium on Deformation Monitoring - JISDM 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4995/jisdm2022.2022.13678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Various measurement techniques and data processing are applied to determine point displacements and deformation of geodetic networks or buildings. Considering classical measurements and analysis of the network deformation, we should realize that the measurements are not “immediate.” The question arises: what happens if a point (or some points) displaces between particular measurements within one epoch. In such a case, the observation set would consist of the observations before and after point displacement, and such hypothetical observation groups can be regarded as related to two (or more) pseudo epochs. The paper's main objective is to examine some estimation methods that would probably deal with such a problem, namely Msplit estimation (in two variants, the squared and the absolute Msplit estimation) and chosen robust methods, namely Huber’s method (example M-estimation) and the Hodges-Lehmann weighted estimation (basic R-estimation). The first approach can provide two (or more) variants of the network point coordinates (here, before and after point movements), providing information about two (or more) states of the network during measurements. In contrast, the robust methods can only decrease the influence of the outliers on the computed network point coordinates. Thus, estimation results would concern only one network state in such a case. The presented empirical analyses show that the better and more realistic results are obtained by applying Msplit estimation. Huber’s method can also provide acceptable results (describing the network state at the epoch beginning) only if the number of observations conducted after the point displacements is not too high.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
经典测量中的点位移-测量之间伪时代的实用方法
各种测量技术和数据处理应用于确定大地测量网或建筑物的点位移和变形。考虑到网络变形的经典测量和分析,我们应该认识到测量不是“即时的”。问题出现了:如果一个点(或一些点)在一个历元内的特定测量之间发生位移会发生什么?在这种情况下,观测集将由点位移前后的观测组成,这种假设的观测组可以看作与两个(或多个)伪时代有关。本文的主要目的是研究一些可能处理此类问题的估计方法,即Msplit估计(在两种变体中,平方和绝对Msplit估计)和选择的鲁棒方法,即Huber方法(示例m -估计)和Hodges-Lehmann加权估计(基本r -估计)。第一种方法可以提供网络点坐标的两个(或更多)变体(这里,在点移动之前和之后),在测量期间提供关于网络的两个(或更多)状态的信息。相比之下,鲁棒方法只能减少异常值对计算的网络点坐标的影响。因此,在这种情况下,估计结果将只涉及一个网络状态。实证分析表明,采用Msplit估计可以获得更好、更真实的结果。Huber的方法也可以提供可接受的结果(描述历元开始时的网络状态),只要在点位移之后进行的观测次数不太高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Landslide monitoring using geotechnical, UAV, GNSS and MTInSAR instrumentation Evaluation of synthetic aperture radar interferometric techniques for monitoring of fast deformation caused by underground mining exploitation Long and close-range terrestrial photogrammetry for rocky landscape deformation monitoring PS-InSAR and UAV technology used in the stability study of Ankang expansive soil airport Deformation analysis in landslides NE Bulgaria using GNSS data complemented by InSAR for better interpretation results
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1