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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials, Volume 35, Number 1(3) (2023)
Copyright(C) MYU K.K.
pp. 307-316
S&M3169 Research Paper of Special Issue
https://doi.org/10.18494/SAM4217
Published: January 31, 2023

Noise Model Analysis of Coordinate Time Series of Reference Station [PDF]

Xiyue Zhang, Yanyan Zeng, Zhengzao Ren, Zhaorong Zhu, and Fenglu Zhang

(Received October 31, 2022; Accepted January 10, 2023)

Keywords: Continuously Operating Reference Stations, time series, noise characteristics, velocity field

To further improve the precision of the Continuously Operating Reference Stations (CORS) coordinate solution, high-precision data processing software was used to process the multi-year observation data of 13 CORS in Beijing, and the original coordinate time series and coordinate residual time series were obtained. Maximum likelihood estimation combined with power spectrum estimation was used to analyze the noise category and the best model of the CORS. The results show that the noise components in the north, east, and up (NEU) directions of the time series include white noise and flicker noise, among which the noise components in the N direction of seven CORS include random walk noise, the noise components in the E direction of one station include random walk noise, and the noise components in the U direction of three CORS include random walk noise. The best noise model of the Beijing CORS base station coordinate time series is the white noise (WN)+flicker noise (FN)+random walk noise (RWN) combined model.

Corresponding author: Xiyue Zhang


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Cite this article
Xiyue Zhang, Yanyan Zeng, Zhengzao Ren, Zhaorong Zhu, and Fenglu Zhang, Noise Model Analysis of Coordinate Time Series of Reference Station, Sens. Mater., Vol. 35, No. 1, 2023, p. 307-316.



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