Sensors, Vol. 21, Pages 1569: Independent Component Extraction from the Incomplete Coordinate Time Series of Regional GNSS Networks

Sensors, Vol. 21, Pages 1569: Independent Component Extraction from the Incomplete Coordinate Time Series of Regional GNSS Networks Sensors doi: 10.3390/s21051569 Authors: Tengfei Feng Yunzhong Shen Fengwei Wang Independent component analysis (ICA) is one of the most effective approaches in extracting independent signals from a global navigation satellite system (GNSS) regional station network. However, ICA requires the involved time series to be complete, thereby the missing data of incomplete time series should be interpolated beforehand. In this contribution, a modified ICA is proposed, by which the missing data are first recovered based on the reversible property between the original time series and decomposed principal components, then the complete time series are further processed with FastICA. To evaluate the performance of the modified ICA for extracting independent components, 24 regional GNSS network stations located in North China from 2011 to 2019 were selected. After the trend, annual and semiannual terms were removed from the GNSS time series, the first two independent components captured 17.42, 18.44 and 17.38% of the total energy for the North, East and Up coordinate components, more than those derived by the iterative ICA that accounted for 16.21%, 17.72% and 16.93%, respectively. Therefore, modified ICA can extract more independent signals than iterative ICA. Subsequently, selecting the 7 stations with less missing data from the network, we repea...
Source: Sensors - Category: Biotechnology Authors: Tags: Technical Note Source Type: research