@article{TuGeWangetal.2014,
  author    = {Tu, Rui and Ge, Maorong and Wang, Rongjiang and Walter, Thomas R.},
  title     = {A new algorithm for tight integration of real-time GPS and strong-motion records, demonstrated on simulated, experimental, and real seismic data},
  series = {Journal of seismology},
  volume    = {18},
  journal   = {Journal of seismology},
  number    = {1},
  publisher = {Springer},
  address   = {Dordrecht},
  issn      = {1383-4649},
  doi       = {10.1007/s10950-013-9408-x},
  pages     = {151 -- 161},
  year      = {2014},
  abstract  = {The complementary advantages of GPS and seismic measurements are well recognized in seismotectonic monitoring studies. Therefore, integrated processing of the two data streams has been proposed recently in an attempt to obtain accurate and reliable information of surface displacements associated with earthquakes. A hitherto still critical issue in the integrated processing is real-time detection and precise estimation of the transient baseline error in the seismic records. Here, we report on a new approach by introducing the seismic acceleration corrected by baseline errors into the state equation system. The correction is performed and regularly updated in short epochs (with increments which may be as short as seconds), so that station position, velocity, and acceleration can be constrained very tightly and baseline error can be estimated as a random-walk process. With the adapted state equation system, our study highlights the use of a new approach developed for integrated processing of GPS and seismic data by means of sequential least-squares adjustment. The efficiency of our approach is demonstrated and validated using simulated, experimental, and real datasets. The latter were collected at collocated GPS and seismic stations around the 4 April 2010, E1 Mayor-Cucapah earthquake (Mw, 7.2). The results have shown that baseline errors of the strong-motion sensors are corrected precisely and high-precision seismic displacements are real-timely obtained by the new approach.},
  language  = {en}
}
@article{TuWangWalteretal.2014,
  author    = {Tu, Rui and Wang, Rongjiang and Walter, Thomas R. and Diao, FaQi},
  title     = {Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter},
  series = {Advances in space research},
  volume    = {54},
  journal   = {Advances in space research},
  number    = {9},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0273-1177},
  doi       = {10.1016/j.asr.2014.07.008},
  pages     = {1924 -- 1932},
  year      = {2014},
  abstract  = {The real-time recognition and precise correction of baseline shifts in strong-motion records is a critical issue for GPS and accelerometer combined processing. This paper proposes a method to adaptively recognize and correct baseline shifts in strong-motion records by utilizing GPS measurements using two phases Kalman filter. By defining four kinds of learning statistics and criteria, the time series of estimated baseline shifts can be divided into four time intervals: initialization, static, transient and permanent. During the time interval in which the transient baseline shift is recognized, the dynamic noise of the Kalman filter system and the length of the baseline shifts estimation window are adaptively adjusted to yield a robust integration solution. The validations from an experimental and real datasets show that acceleration baseline shifts can be precisely recognized and corrected, thus, the combined system adaptively adjusted the estimation strategy to get a more robust solution. (C) 2014 COSPAR. Published by Elsevier Ltd. All rights reserved.},
  language  = {en}
}
@article{Tu2014,
  author    = {Tu, Rui},
  title     = {Fast determination of displacement by PPP velocity estimation},
  series = {Geophysical journal international},
  volume    = {196},
  journal   = {Geophysical journal international},
  number    = {3},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0956-540X},
  doi       = {10.1093/gji/ggt480},
  pages     = {1397 -- 1401},
  year      = {2014},
  abstract  = {Global Positioning System (GPS) has been proven to be an effective tool to retrieve high-precision displacement for the natural hazard monitoring. The network positioning and Precise Point Positioning (PPP) are the two basic approaches for its data solution, but the former one can only get a relative displacement within the local reference frame and requires a complex and continuously linked infrastructure, and the latter one with a long convergence time to obtain the absolute displacements within the global reference frame. To overcome these drawbacks, this paper proposed a method of fast determining the displacement by PPP velocity estimation (PPPVE). The key of the approach is that the velocity vector parameters are not correlated with other unknown parameters, such as ambiguities and atmosphere, so they can be fast and accurately estimated and integrated into displacements. The validation shows that the displacement can be provided with a precision of 1-2 cm in 1 min by PPPVE. In additional, the Kalman smoothing estimation can be used to improve the PPP solution.},
  language  = {en}
}
@article{TuWangLiu2016,
  author    = {Tu, Rui and Wang, L. and Liu, Z.},
  title     = {Real time monitoring ground motion using GPS with real time corrections},
  series = {Survey Review},
  volume    = {48},
  journal   = {Survey Review},
  publisher = {Wiley},
  address   = {Abingdon},
  issn      = {0039-6265},
  doi       = {10.1179/1752270614Y.0000000141},
  pages     = {79 -- 85},
  year      = {2016},
  abstract  = {The high rate GPS velocity determination technology which is based on the broadcast ephemeris and epoch differenced model can retrieve displacement of ground motion with the precision of a few centimetres to decimetres in real time. Moreover, the precision of the recovered displacement can be improved if the un-modelled errors such as broadcast ephemeris residuals, atmospheric residuals, multipath effects and high frequency noise are tackled more accurately. In this paper, we propose a method to improve the precision of the recovered displacement by appropriately making use of reference station corrections. For the reference stations, the coordinates are highly constrained to extract the error corrections that are to be broadcast via a communication link to the rover. After correcting the rover's observations, some errors such as ephemeris residuals and atmospheric residuals are effectively eliminated or at least reduced. This improves the accuracy of the observations and thus enhances the reliability of the velocity estimation. The displacement can be recovered by integrating the estimated velocity after de-trending using a linear trend that is caused by the un-corrected residuals. The series of validation results in the experiment have shown that the displacement of the simulated motion can be real time recovered with a precision of 1-2 cm, and is thus applicable for real time monitoring of the ground motion.},
  language  = {en}
}
@article{TuGeZhangetal.2013,
  author    = {Tu, Rui and Ge, Maorong and Zhang, Hongping and Huang, Guanwen},
  title     = {The realization and convergence analysis of combined PPP based on raw observation},
  series = {Advances in space research},
  volume    = {52},
  journal   = {Advances in space research},
  number    = {1},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0273-1177},
  doi       = {10.1016/j.asr.2013.03.005},
  pages     = {211 -- 221},
  year      = {2013},
  abstract  = {In order to speed up Precise Point Positioning (PPP)'s convergence, a combined PPP method with GPS and GLONASS which is based on using raw observations is proposed, and the positioning results and convergence time have been compared with that of single system. The ionospheric delays and receiver's Differential Code Bias (DCB) corrections are estimated as unknown parameters in this method. The numerical results show that the combined PPP has not caused significant impacts on the final solutions, but it greatly improved Position Dilution of Precision (PDOP) and convergence speed and enhanced the reliability of the solution. Meanwhile, the convergence speed is greatly influenced by the receiver's DCB, positioning results in horizontal which are better than 10 cm can be realized within 10 min. In addition, the ionosphere and DCB products can be provided with high precision.},
  language  = {en}
}
@article{TuChen2014,
  author    = {Tu, Rui and Chen, Kejie},
  title     = {Tightly integrated processing of high-rate GPS and accelerometer observations by real-time estimation of transient baseline shifts},
  series = {The journal of navigation},
  volume    = {67},
  journal   = {The journal of navigation},
  number    = {5},
  publisher = {Cambridge Univ. Press},
  address   = {New York},
  issn      = {0373-4633},
  doi       = {10.1017/S0373463314000150},
  pages     = {869 -- 880},
  year      = {2014},
  abstract  = {The complementary advantages of high-rate Global Positioning System (GPS) and accelerometer observations for measuring seismic ground motion have been recognised in previous research. Here we propose an approach of tight integration of GPS and accelerometer measurements. The baseline shifts of the accelerometer are introduced as unknown parameters and estimated by a random walk process in the Precise Point Positioning (PPP) solution. To demonstrate the performance of the new strategy, we carried out several experiments using collocated GPS and accelerometer. The experimental results show that the baseline shifts of the accelerometer are automatically corrected, and high precision coseismic information of strong ground motion can be obtained in real-time. Additionally, the convergence and precision of the PPP is improved by the combined solution.},
  language  = {en}
}