Preprocessing of GPS Coordinate Sequence Based on Singular Spectrum Analysis

4th International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Ren, Yingying^1 ; Lian, Lizhen^2 ; Wang, Jiexian^1 ; Wang, Hu^3

College of Surveying and GeoInformatics, Tongji University, Shanghai

200092, China^1

CAS Key Laboratory of Planetary Sciences, Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai

20030, China^2

Chinese Academy of Surveying and Mapping, Beijing

100830, China^3

关键词: Gross error detection;    Intrinsic characteristics;    Missing data recoveries;    Nonlinear signals;    Piecewise linear;    Pre-processing method;    Real data analysis;    Singular spectrum analysis;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/237/3/032043/pdf
DOI  :  10.1088/1755-1315/237/3/032043

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Since it is inevitable existence of unknown mutation signals, gross error and data missing in the GPS station coordinates, while the nonlinear signals and misalignment are also neglected by means of piecewise linear detection, thus a novel algorithm called jump determination scheme, which is based on singular spectrum analysis (SSA), is proposed here. The results of real data analysis and simulation tests indicate that the SSA-based pre-processing method has properly detected the gross error and recovered the missing data. Meanwhile, owing to taking into account the correlation in the position time series, it can effectively avoid the influence of gross error on the accurate determination of each uncertain jump. In addition, it can retain the intrinsic characteristics in station coordinates, which has vital significance for the gross error detection and missing data recovery. By this new method, even if the missing rate of data reaches 10% or more, we can eliminate the gross error and then obtain complete data with an accuracy of better than 5 mm and 1 cm for the horizontal components and the height component, respectively.