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Ma X.,Tongji University | Shen Y.,Center for Spatial Information Science and Sustainable Development
Lecture Notes in Electrical Engineering | Year: 2013

In this paper, we carried out GPS and BeiDou relative positioning with our developed software using the real data collected in Beijing and Shanghai, respectively, and assessed the accuracy of single epoch baseline solution of the two systems. For short baseline, the relative positioning accuracies of the two systems are basically the same, and the vertical accuracy of the baseline of BeiDou is better than that of GPS. The solved time series errors mainly contain the multipath error and random noise. We used wavelet filtering to extract multipath error according to the frequency characteristics of the random noise and multipath errors. Subsequently, the analysis of GPS and BeiDou multipath was carried out to find the differences between them. Finally, sidereal filtering based on the orbit characteristics of BeiDou was used to eliminate multipath error and improve the relative positioning accuracy. The results showed that the accuracy of relative positioning for short baselines can improve up to 10 % after the multipath error is filtered out. © 2013 Springer-Verlag Berlin Heidelberg. Source

Chen Q.,Tongji University | Chen Q.,Hong Kong Polytechnic University | Chen Q.,Center for Spatial Information Science and Sustainable Development | Shen Y.,Tongji University | And 3 more authors.
Journal of Geodesy | Year: 2016

The main contribution of this study is to improve the GRACE gravity field solution by taking errors of non-conservative acceleration and attitude observations into account. Unlike previous studies, the errors of the attitude and non-conservative acceleration data, and gravity field parameters, as well as accelerometer biases are estimated by means of weighted least squares adjustment. Then we compute a new time series of monthly gravity field models complete to degree and order 60 covering the period Jan. 2003 to Dec. 2012 from the twin GRACE satellites’ data. The derived GRACE solution (called Tongji-GRACE02) is compared in terms of geoid degree variances and temporal mass changes with the other GRACE solutions, namely CSR RL05, GFZ RL05a, and JPL RL05. The results show that (1) the global mass signals of Tongji-GRACE02 are generally consistent with those of CSR RL05, GFZ RL05a, and JPL RL05; (2) compared to CSR RL05, the noise of Tongji-GRACE02 is reduced by about 21 % over ocean when only using 300 km Gaussian smoothing, and 60 % or more over deserts (Australia, Kalahari, Karakum and Thar) without using Gaussian smoothing and decorrelation filtering; and (3) for all examples, the noise reductions are more significant than signal reductions, no matter whether smoothing and filtering are applied or not. The comparison with GLDAS data supports that the signals of Tongji-GRACE02 over St. Lawrence River basin are close to those from CSR RL05, GFZ RL05a and JPL RL05, while the GLDAS result shows the best agreement with the Tongji-GRACE02 result. © 2016, Springer-Verlag Berlin Heidelberg. Source

Li W.,Tongji University | Li W.,Center for Spatial Information Science and Sustainable Development | Shen Y.,Tongji University | Li B.,Tongji University
Acta Geodaetica et Geophysica | Year: 2015

Principal component analysis (PCA) is a powerful tool for extracting common mode errors from the position time series of a regional station network determined by global navigation satellite system (GNSS). It is implicitly based on the assumption that a time series dataset contains temporally uniform white noise. Since the position time series of a regional station network are not uniform and could have data gaps, this paper develops a PCA-based weighted spatiotemporal filtering (WSF) approach by taking into account the positioning formal error of daily solution and the data gaps in time series. The position time series of 27 GNSS stations of the Crust Motion Observation Network of China are analyzed to demonstrate the performance of WSF approach, and also compared with the modified PCA technique in Shen et al. (J Geod 88:1-12, 2014). It shows that the WSF approach outperforms the modified PCA at 21, 19 and 17 out of the total 27 stations for north, east and up components, respectively. The average formal standard deviation of unit weight derived from WSF and modified PCA are 2.12, 2.42, 5.88 and 2.21, 2.52, 6.05 for north, east and up components, respectively; the relative improvements are 4.1, 4.0 and 2.8 %. Moreover, two simulations of a network with 4 stations are processed to show the performance of WSF. The results show that WSF provides better results for all coordinate components of all stations when the local effects are small or negligible. For cases when the local effects becoming larger, the WSF performs better than the modified PCA from the statistical point of view. From the real and synthetic time series analysis results, it is reasonable to conclude that the positioning formal error of daily solution should be considered in spatiotemporal filtering. © 2015, Akadémiai Kiadó. Source

Chen Q.,Tongji University | Chen Q.,Hong Kong Polytechnic University | Chen Q.,Center for Spatial Information Science and Sustainable Development | Shen Y.,Tongji University | And 3 more authors.
Advances in Space Research | Year: 2015

The modified short arc approach, where the position vector in force model are regarded as pseudo observation, is implemented in the SAtellite Gravimetry Analysis Software (SAGAS) developed by Tongji university. Based on the SAGAS platform, a static gravity field model (namely Tongji-GRACE01) complete to degree and order 160 is computed from 49 months of real GRACE Level-1B data spanning the period 2003-2007 (including the observations of K-band range-rate, reduced dynamic orbits, non-conservative accelerations and altitudes). The Tongji-GRACE01 model is compared with the recent GRACE-only models (such as GGM05S, AIUB-GRACE03S, ITG-GRACE03, ITG-GRACE2010S, and ITSG-GRACE2014S) and validated with GPS-leveling data sets in different countries. The results show that the Tongji-GRACE01 model has a considered quality as GGM05S, AIUB-GRACE03S and ITG-GRACE03. The Tongji-GRACE01 model is available at the International Centre for Global Earth Models (ICGEM) web page (http://icgem.gfz-potsdam.de/ICGEM/). © 2015 COSPAR. Published by Elsevier Ltd. All rights reserved. Source

Shen Y.,Tongji University | Peng F.,Tongji University | Peng F.,Center for Spatial Information Science and Sustainable Development | Li B.,Tongji University
Nonlinear Processes in Geophysics | Year: 2015

Singular spectrum analysis (SSA) is a powerful technique for time series analysis. Based on the property that the original time series can be reproduced from its principal components, this contribution develops an improved SSA (ISSA) for processing the incomplete time series and the modified SSA (SSAM) of Schoellhamer (2001) is its special case. The approach is evaluated with the synthetic and real incomplete time series data of suspended-sediment concentration from San Francisco Bay. The result from the synthetic time series with missing data shows that the relative errors of the principal components reconstructed by ISSA are much smaller than those reconstructed by SSAM. Moreover, when the percentage of the missing data over the whole time series reaches 60 %, the improvements of relative errors are up to 19.64, 41.34, 23.27 and 50.30 % for the first four principal components, respectively. Both the mean absolute error and mean root mean squared error of the reconstructed time series by ISSA are also smaller than those by SSAM. The respective improvements are 34.45 and 33.91 % when the missing data accounts for 60 %. The results from real incomplete time series also show that the standard deviation (SD) derived by ISSA is 12.27 mg L-1, smaller than the 13.48 mg L-1 derived by SSAM. © Author(s) 2015. Source

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