Weighted empirical mode decomposition for processing GNSS position time series with the consideration of formal errors

Title:

Weighted empirical mode decomposition for processing GNSS position time series with the consideration of formal errors

Creator:

Qiu, Xiaomeng, Wang, Fengwei, Zhou, Yunqi, and Zhou, Shijian

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:31705652-7adc-4828-8779-1d1298f6eec4
uuid:31705652-7adc-4828-8779-1d1298f6eec4
issn:1214-9705
doi:10.13168/AGG.2021.0028

Subject:

satelitní navigační systémy, satellite navigation systems, weighted empirical mode decomposition, signal extraction, GNSS position time series, empirical mode decomposition, formal errors, 7, and 551

Type:

model:article and TEXT

Format:

print, bez média, and svazek

Description:

Empirical Mode Decomposition (EMD) is suitable to process the nonlinear and non-stationary time series for filtering noise out to extract the signals. The formal errors are provided along with Global Navigation Satellite System (GNSS) position time series, however, not being considered by the traditional EMD. In this contribution, we proposed a modified approach that called weighted Empirical Mode Decomposition (weighted EMD) to extract signals from GNSS position time series, by constructing the weight factors based on the formal errors. The position time series over the period from 2011 to 2018 of six permanent stations (SCBZ, SCJU, SCMN, HLFY, FJPT, SNXY) were analyzed by weighted EMD, as well as the traditional EMD. The results show that weighted EMD can extract more signals than traditional EMD from original GNSS position time series. Additionally, the fitting errors were reduced 14.52 %, 12.25 % and 8.06 % for North, East and Up components for weighted EMD relative to traditional EMD, respectively. Moreover, 100 simulations of four stations are further carried out to validate the performances of weighted EMD and traditional EMD. The mean Root Mean Squared Errors (RMSEs) are reduced from traditional EMD to weighted EMD with the reductions of 9.08 %, 9.63 % and 6.84 % for East, North and Up components, respectively, which highlights the necessity of considering the formal errors. Therefore, it reasonable to conclude that weighted EMD can extract the signals more than traditional EMD, which can be suggested to analyze GNSS position time series with formal errors., Xiaomeng Qiu, Fengwei Wang, Yunqi Zhou and Shijian Zhou., and Obsahuje bibliografii

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

399-408

Source:

Acta geodynamica et geomaterialia : | 2021 Volume:18 | Number:3 (203)

Harvested from:

CDK

Metadata only:

false