Global Positioning System Network Data Research Articles

Medium‐Scale Traveling Ionospheric Disturbances Induced by Typhoon Chan‐hom Over China

AbstractThis paper reports the ionospheric response to Typhoon Chan‐hom using Global Positioning System network data from China, combined with observations of an ionosonde chain. Two medium‐scale traveling ionospheric disturbances (MSTIDs) were observed around the two landing times of Typhoon Chan‐hom. The MSTID with a phase fronts aligned in the north‐south direction was detected on the east coast of China at 16:50–18:40 UT on 11 July 2015 and moved westward with a mean horizontal phase velocity of 268 m/s and period of 56 min. Then the concentric MSTID appeared on the northeast of China at 01:50–05:10 UT on 13 July 2015 and propagated in the radial direction with average horizontal phase velocity of 143 m/s and period of 45 min. There may be some connections between the north‐south‐aligned MSTID and the electrodynamical coupling of the sporadic E layer and the F layer, while the concentric MSTID may be caused by the concentric gravity waves resulting from the bodyforces related with the typhoon.

IONOLAB-MAP: An automatic spatial interpolation algorithm for total electron content

Investigation of the variability of total electron content (TEC) is one of the most important parameters of the observation and monitoring of space weather, which is the main cause of signal disturbance in space-based communication, positioning, and navigation systems. TEC is defined as the total number of electrons on a ray path. The Global Positioning System (GPS) provides a cost-effective solution for the estimation of TEC. Due to various physical and operational disturbances, TEC may have temporal and spatial domain gaps. Global ionospheric maps (GIMs) provide worldwide TEC with 1- to 2-h temporal resolution and $2.5^{\circ}\, \times 5^{\circ}$ spatial resolution in latitude and longitude, respectively. The GIM-TEC with the highest possible accuracy can be obtained 10 days after the recording of the signals. Therefore, a high-resolution and accurate interpolation of TEC is necessary to image and monitor the regional distribution of TEC in near-real time. In this study, a novel spatiotemporal interpolation algorithm with automatic gridding is developed for 2-D TEC imaging by data fusion of GPS-TEC and GIM-TEC. The algorithm automatically implements optimum spatial resolution and desired temporal resolution with universal kriging with linear trend for midlatitude regions and ordinary kriging for other regions. The theoretical semivariogram function is estimated from GPS network data using a Matern family, whose parameters are determined with a particle swarm optimization algorithm. The developed algorithm is applied to the Turkish National Permanent GPS Network (TNPGN-Active), a dense midlatitude GPS network. For the first time in the literature, high spatial resolution TEC maps are obtained between May 2009 and May 2012 with a 2.5-min temporal update period. These TEC maps will be used to investigate the spatiotemporal variability of the ionosphere over the diurnal and annual trend structure, including seasonal anomalies and geomagnetic and seismic disturbances over ionosphere.

Orientation and Displacement Detection for Smartphone Device Based IMUs

Commonly, navigation uses global positioning system/network (GPS) signals to determine location. In addition, GPS data can be collected over time to determine the path taken. In spite of the ubiquity of GPS signals on the earth's surface, there are certain locations where GPS signals are not available, such as inside buildings or tunnels. Therefore, to determine accurate positioning in areas where the GPS signals are unavailable, an inertial measurement unit (IMU) can be used in conjunction with the GPS data. Modern IMUs are small enough to be contained in Microelectromechanical systems (MEMS) chips, including smartphone devices, such as iPhones. This paper studies the integration between the GPS signal and the collected data from smartphones' MEMS sensors. It also investigates the possibility of using the integrated GPS/MEMS information to estimate route when the GPS signal is missing. We propose estimating the missing GPS signal by sensor integration of smartphone data. This paper would enhance the GPS navigation to determine exact positions even in the case of signal failures. Modern IMUs are expensive, and this paper shows that GPS/IMU integration can be accomplished with off-the-shelf navigational components. This paper proposes a novel technique for estimating the missing GPS route by integrating data from the sensors available in modern smartphones.

Developing travel time estimation methods using sparse GPS data

ABSTRACTExisting methods of estimating travel time from GPS data are not able to simultaneously take account of the issues related to uncertainties associated with GPS and spatial road network data. Moreover, they typically depend upon high-frequency data sources from specialist data providers, which can be expensive and are not always readily available. The study reported here therefore sought to better estimate travel time using “readily available” vehicle trajectory data from moving sensors such as buses, taxis, and logistical vehicles equipped with GPS in “near” real time. To do this, accurate locations of vehicles on a link were first map-matched to reduce the positioning errors associated with GPS and digital road maps. Two mathematical methods were then developed to estimate link travel times from map-matched GPS fixes, vehicle speeds, and network connectivity information with a special focus on sampling frequencies, vehicle penetration rates, and time window lengths. Global positioning system (GPS) data from Interstate I-880 (California) for a total of 73 vehicles over 6 h were obtained from the University of California Berkeley's Mobile Century Project, and these were used to evaluate several travel time estimation methods, the results of which were then validated against reference travel time data collected from high resolution video cameras. The results indicate that vehicle penetration rates, data sampling frequencies, vehicle coverage on the links, and time window lengths all influence the accuracy of link travel time estimation. The performance was found to be best in the 5-min time window length and for a GPS sampling frequency of 60 s.

Influences of crustal thickening in the Tibetan Plateau on loading modeling and inversion associated with water storage variation

We use the average crustal structure of the CRUST1.0 model for the Tibetan Plateau to establish a realistic earth model termed as TC1P, and data from the Global Land Data Assimilation System (GLDAS) hydrology model and Gravity Recovery and Climate Experiment (GRACE) data, to generate the hydrology signals assumed in this study. Modeling of surface radial displacements and gravity variation is performed using both TC1P and the global Preliminary Reference Earth Model (PREM). Furthermore, inversions of the hydrology signals based on simulated Global Positioning System (GPS) and GRACE data are performed using PREM. Results show that crust in TC1P is harder and softer than that in PREM above and below a depth of 15 km, respectively, causing larger differences in the computed load Love numbers and loading Green's functions. When annual hydrology signals are assumed, the differences of the radial displacements are found to be as large as approximately 0.6 mm for the truncated degree of 180; while for hydrology-trend signals the differences are very small. When annual hydrology signals and the trends are assumed, the differences in the surface gravity variation are very small. It is considered that TC1P can be used to efficiently remove the hydrological effects on the monitoring of crustal movement. It was also found that when PREM is used inappropriately, the inversion of the hydrology signals from simulated annual GPS signals can only recover approximately 88.0% of the annual hydrology signals for the truncated degree of 180, and the inversion of hydrology signals from the simulated trend GPS signals can recover approximately 92.5% for the truncated degree of 90. However, when using the simulated GRACE data, it is possible to recover almost 100%. Therefore, in future, the TC1P model can be used in the inversions of hydrology signals based on GPS network data. PREM is also valid for use with inversions of hydrology signals from GRACE data at resolutions of approximately 220 km and larger.

Source Process of the 2011 Tohoku Earthquake Estimated from the Joint Inversion of Teleseismic Body Waves and Geodetic Data Including Seafloor Observation Data: Source Model with Enhanced Reliability by Using Objectively Determined Inversion Settings

Research Article| May 01, 2013 Source Process of the 2011 Tohoku Earthquake Estimated from the Joint Inversion of Teleseismic Body Waves and Geodetic Data Including Seafloor Observation Data: Source Model with Enhanced Reliability by Using Objectively Determined Inversion Settings Hisahiko Kubo; Hisahiko Kubo Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto, 611‐0011, Japankubo.hisahiko.26a@st.kyoto-u.ac.jp Search for other works by this author on: GSW Google Scholar Yasumaro Kakehi Yasumaro Kakehi Graduate School of Science, Kobe University, 1‐1 Rokkodai‐cho, Nada, Kobe, Hyogo 657‐8501, Japankakehi@kobe-u.ac.jp Search for other works by this author on: GSW Google Scholar Author and Article Information Hisahiko Kubo Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji, Kyoto, 611‐0011, Japankubo.hisahiko.26a@st.kyoto-u.ac.jp Yasumaro Kakehi Graduate School of Science, Kobe University, 1‐1 Rokkodai‐cho, Nada, Kobe, Hyogo 657‐8501, Japankakehi@kobe-u.ac.jp Publisher: Seismological Society of America First Online: 14 Jul 2017 Online ISSN: 1943-3573 Print ISSN: 0037-1106 Bulletin of the Seismological Society of America (2013) 103 (2B): 1195–1220. https://doi.org/10.1785/0120120113 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Hisahiko Kubo, Yasumaro Kakehi; Source Process of the 2011 Tohoku Earthquake Estimated from the Joint Inversion of Teleseismic Body Waves and Geodetic Data Including Seafloor Observation Data: Source Model with Enhanced Reliability by Using Objectively Determined Inversion Settings. Bulletin of the Seismological Society of America 2013;; 103 (2B): 1195–1220. doi: https://doi.org/10.1785/0120120113 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Abstract The rupture process of the 2011 Tohoku earthquake is estimated from the joint inversion of teleseismic body waves and geodetic data using multiple time‐window analysis. To enhance the reliability of the inversion solution, two important inversion‐setting parameters that control the spatiotemporal slip distribution, the maximum slip duration of each subfault (Tsd) and the propagation velocity of the first time window (Vftw), are determined by objective criteria. By performing a semblance analysis of small‐aperture seismic array data of near‐source strong motion waveforms, Tsd is determined to be 100 s. Vftw is determined to be 2.0 km/s from the matching of the teleseismic and geodetic slip models. The spatial resolution of geodetic inversion is significantly improved by using seafloor crustal deformation data in the source area in addition to the terrestrial Global Positioning System network data. The estimated seismic moment and the maximum slip are 3.4×1022 N·m (Mw=9.0) and 43 m, respectively. The total rupture duration is ∼150 s. Large slip is seen in the shallow part of the fault surface, including the hypocenter, and its spatial extent along the trench axis is ∼300 km. This model is consistent with the results of bathymetric surveys and the slip models from tsunami data. The relationships among the fault parameters of the characterized source model of the 2011 Tohoku earthquake suggest the possibility that saturation of fault width occurs for this huge earthquake.Online Material: Text S1 denotes the explanation of how the rupture propagation in the dip direction affects the estimated value of maximum slip duration (Tsd). Table S1 denotes the detailed information of the teleseismic stations. Table S2 denotes the detailed information of the terrestrial geodetic stations. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Stress inversion method for predicting local stress distribution of body in two-dimensional state of plane stress or strain

The stress inversion method is aimed at predicting a local stress distribution from by measuring a displacement distribution. This paper presents the formulation of the method and some examples of the application. The key point of the stress inversion method is that, for a body in state of plane strain or stress, only three stress components are non-trivial and they satisfy two equations of equilibrium. Hence, the three stress components can be determined if one relation between stress and strain is known and a strain distribution is given. Numerical simulation and model experiment of a material test are made, and it is shown that local stress and constitutive relations are found by applying the stress inversion method. The application of the method to the nation-wide array data of the global positioning system network data is also presented.

Ionospheric effects of the solar flares of September 23, 1998 and July 29, 1999 as deduced from global GPS network data

This paper presents data from first global positioning system (GPS) measurements of global response of the ionosphere to solar flares of September 23, 1998 and July 29, 1999. The analysis used novel technology of a global detection of ionospheric effects from solar flares as developed by one of the authors (Afraimovich, Radio Sci. 35 (2000) 1417). The essence of the method is that use is made of appropriate filtering and a coherent processing of variations in total electron content (TEC) in the ionosphere which is determined from GPS data, simultaneously for the entire set of visible (over a given time interval) GPS satellites at all stations used in the analysis. It was found that fluctuations of TEC, obtained by removing the linear trend of TEC with a time window of about 5 min, are coherent for all stations and the line-of-sight to the GPS satellites on the dayside of the Earth. The time profile of TEC responses is similar to the time behavior of hard X-ray emission variations during flares if the relaxation time of electron density disturbances in the ionosphere of order 50–100 s is introduced. No such effect on the nightside of the Earth has been detected yet.