Regression and hypothesis tests for multivariate GNSS state time series

Feng, Yanming (2012) Regression and hypothesis tests for multivariate GNSS state time series. Journal of Global Positioning Systems, 11(1), pp. 33-45.

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A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

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ID Code: 58740
Item Type: Journal Article
Refereed: Yes
Keywords: GNSS state time series, univariate analysis, multivariate analysis, T-squared statistics
ISSN: 1446-3156
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Stochastic Analysis and Modelling (010406)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > GEOMATIC ENGINEERING (090900) > Navigation and Position Fixing (090904)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2012 The International Association of Chinese Professionals in Global Positioning Systems (CPGPS)
Deposited On: 27 Mar 2013 23:35
Last Modified: 06 Apr 2013 20:43

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