基于LWR-Pettitt算法的GNSS变形信息的识别与预警

doi:10.13474/j.cnki.11-2246.2021.0156

测绘通报 ›› 2021, Vol. 0 ›› Issue (5): 124-128,154.doi: 10.13474/j.cnki.11-2246.2021.0156

基于LWR-Pettitt算法的GNSS变形信息的识别与预警

段伟¹, 王敏¹, 吴昊², 刘超²

1. 南京市测绘勘察研究院股份有限公司, 江苏南京 210019;
2. 安徽理工大学测绘学院, 安徽淮南 232001

收稿日期:2020-06-23 发布日期:2021-05-28
作者简介:段伟(1985-),男,硕士,高级工程师,主要研究方向为工程测量、轨道交通自动化变形监测、三维激光扫描等。E-mail:306132870@qq.com
基金资助:
南京市测绘勘察研究院股份有限公司科研项目(2020RD09)

Recognition and early warning of deformation information in GNSS coordinate series based on the LWR-Pettitt method

DUAN Wei¹, WANG Min¹, WU Hao², LIU Chao²

1. Nanjing Institute of Surveying, Mapping & Geotechnical Investigation, Co., Ltd., Nanjing 210019, China;
2. School of Geomatics, Anhui University of Science & Technology, Huainan 232001, China

Received:2020-06-23 Published:2021-05-28

摘要/Abstract

摘要： 针对GNSS变形监测的数据通常无特定的分布特性,不利于建立具有普遍性的统计量,本文引入非参数检验中的Pettitt检验方法建立统计量,进行GNSS监测序列中变形信息的识别与预警。同时,针对Pettitt检验方法中存在统计量振幅波动较大,并且只能识别单个变形信息的问题,基于局部加权回归法LWR,对Pettitt检验中统计量与阈值判断方法进行优化,提出一种新的LWR-Pettitt算法,并用于GNSS变形信息识别与预警。试验结果表明,对于不同的测试数据,新方法均可有效地识别变形信息的发生位置,特别对于趋势型变形;而对于突变型变形,新方法可有效地识别2倍标准差以上的连续变形信息。

关键词: GNSS, LWR, Pettitt, 变形监测, 变形预警

Abstract: GNSS deformation monitoring data usually has no specific distribution characteristics, which is not conducive to the establishment of universal statistics. As a non-parametric test method, the Pettitt test is introduced to establish statistics of GNSS deformation monitoring data, and then the deformation information identification and early warning are carried out. However, the statistics constructed by the Pettitt test always have large fluctuation, and can only be used to identify the single deformation information. Therefore, a new method named LWR (Locally Weighted Regression)-Pettitt is proposed to optimize the statistics and threshold judgment method in the Pettitt test, and is used for GNSS deformation information identification and early warning in this paper. The experimental results show that the proposed method can identify the location of deformation information effectively, especially for trend-type deformation information, but for the abrupt-type deformation information, it can only identify the continuous deformation information more than two-fold standard deviation equivalent deformation.

Key words: GNSS, Locally Weighted Regression, Pettitt, deformation monitoring, deformation early warning

中图分类号:

P208

段伟, 王敏, 吴昊, 刘超. 基于LWR-Pettitt算法的GNSS变形信息的识别与预警[J]. 测绘通报, 2021, 0(5): 124-128,154.

DUAN Wei, WANG Min, WU Hao, LIU Chao. Recognition and early warning of deformation information in GNSS coordinate series based on the LWR-Pettitt method[J]. Bulletin of Surveying and Mapping, 2021, 0(5): 124-128,154.

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基于LWR-Pettitt算法的GNSS变形信息的识别与预警

Recognition and early warning of deformation information in GNSS coordinate series based on the LWR-Pettitt method

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