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• W4379468113 abstract "Singular spectrum analysis is widely used in geodetic time series analysis. However, when extracting time-varying periodic signals from a large number of Global Navigation Satellite System (GNSS) time series, the selection of appropriate embedding window size and principal components makes this method cumbersome and inefficient. To improve the efficiency and accuracy of singular spectrum analysis, this paper proposes an adaptive singular spectrum analysis method by combining spectrum analysis with a new trace matrix. The running time and correlation analysis indicate that the proposed method can adaptively set the embedding window size to extract the time-varying periodic signals from GNSS time series, and the extraction efficiency of a single time series is six times that of singular spectrum analysis. The method is also accurate and more suitable for time-varying periodic signal analysis of global GNSS sites." @default.
• W4379468113 created "2023-06-07" @default.
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• W4379468113 date "2023-06-01" @default.
• W4379468113 modified "2023-10-16" @default.
• W4379468113 title "Periodic signal extraction of GNSS height time series based on adaptive singular spectrum analysis" @default.
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• W4379468113 doi "https://doi.org/10.1016/j.geog.2023.04.003" @default.
• W4379468113 hasPublicationYear "2023" @default.
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