TY - JOUR A1 - Tu, Rui A1 - Wang, Rongjiang A1 - Walter, Thomas R. A1 - Diao, FaQi T1 - Adaptive recognition and correction of baseline shifts from collocated GPS and accelerometer using two phases Kalman filter JF - Advances in space research N2 - 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. KW - GPS KW - Strong-motion KW - Baseline shift KW - Kalman filter KW - Integration Y1 - 2014 U6 - https://doi.org/10.1016/j.asr.2014.07.008 SN - 0273-1177 SN - 1879-1948 VL - 54 IS - 9 SP - 1924 EP - 1932 PB - Elsevier CY - Oxford ER - TY - JOUR A1 - Tu, Rui A1 - Ge, Maorong A1 - Wang, Rongjiang A1 - Walter, Thomas R. T1 - A new algorithm for tight integration of real-time GPS and strong-motion records, demonstrated on simulated, experimental, and real seismic data JF - Journal of seismology N2 - 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. KW - High-rateGPS KW - Strong-motion records KW - Baseline error KW - Tight integration KW - Precise point positioning Y1 - 2014 U6 - https://doi.org/10.1007/s10950-013-9408-x SN - 1383-4649 SN - 1573-157X VL - 18 IS - 1 SP - 151 EP - 161 PB - Springer CY - Dordrecht ER -