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342 results for “gnss”
Validation of Peak Ground Velocities Recorded on Very-high rate GNSS Against NGA-West2 Ground Motion Models: Dataset
<p>Contains all the data files for the manuscript of the same name.</p>
Erebus GNSS timeseries with respect to stable Antarctica
<p>GNSS timeseries for Ross Island / Erebus volcano in an Antarctica stable reference frame. Files contain fields for</p> <p>dec year | dE (mm) | dN (mm) | dU (mm) | sigE (mm) | sigN (mm) | sigU (mm) | Ren | Reu | Rnu | seconds past J2000 | year | month | day | hour | min | second | solution path<br> <br> Details on processing and corrections are explained in</p> <p>Grapenthin, R., P. Kyle, R.C. Aster, M. Angarita, T. Wilson, J. Chaput, Deformation at the open-vent Erebus volcano, Antarctica, from more than 20 years of GNSS Observations, (under consideration for) JVGR.</p> <p> </p> <p> </p>
Input data for manuscript "SNR-based GNSS reflectometry for coastal sea-level altimetry – Results from the first IAG inter-comparison campaign"
<p>GNSS data collected at station GTGU for one year (2015.5-2016.5) and nearby tide gauge data.</p> <p>Note: the antenna position in the header file, expressed in global Cartesian coordinates, corresponds inadvertently to integer values of latitude, longitude, and altitude (57.0°, 11.0°, 0.0 m); non-truncated values are as follows: 57.3929549°, 11.9134886°, 40.420 m.</p>
Output data for manuscript "SNR-based GNSS reflectometry for coastal sea-level altimetry – Results from the first IAG inter-comparison campaign"
<p>GNSS-R sea level time series and ancillary information about periods with incomplete GNSS data.</p>
3D Coseismic Deformation of the 2023 Türkiye Mw7.8-7.5 Earthquake Doublet Deduced from High-rate GNSS Observations
<p>3D displacements of the 2023 Türkiye Mw7.8-7.5 earthquakes derived from high-rate GNSS data.</p> <p>This Zenodo repository contains 3D displacements for the paper "Coseismic Deformation and Kinematic Rupture Process of the 2023 Türkiye Mw7.8-7.5 Earthquake Doublet Deduced from High-rate GNSS Observations " by Dong et al. in Geophysical Journal International. If you use any of the data or models please cite it accordingly.</p> <p>For any questions or issues, email Zhihua Dong at <a href="mailto:dmelgarm@uoregon.edu">dongzhihua93@163.com</a>. </p>
Strain partitioning, transfer and implications for ongoing processes of the intra-continental graben formation in the NW margin of the Ordos block, China: insights from densified GNSS measurements
<p><strong><span>GNSS data and processing</span></strong></p> <p><strong><span>1. Intensive observations</span></strong></p> <p><span>In this study, in addition to GNSS data surveyed around the Ordos block provided by <span>Hao et al. (2021)</span>, we collected GNSS data surveyed west of 103°E from </span><span>Phases</span><span> I and II of <span>the Crustal Movement Observation Network of China (CMONOC)</span></span><span>, which</span><span> has conducted measurements every one or two years from 1999 to 2019.</span><span> In particular</span><span>, we also collected data from 70 GNSS sites </span><span>deployed by<span> <a name="OLE_LINK49"></a><a name="OLE_LINK50"></a><a name="OLE_LINK82"></a><span><span>the National Geodetic Control Network of China (NGCNC)</span></span>. These sites were distributed in the northwestern boundary of the Ordos block and the interior of the Alashan and Ejina blocks and </span></span><span>first</span><span> measured 72 hours of data in 2014 or 2015. From September to October 2021, we conducted the second set of measurements for these GNSS sites of 96 continuous hours.</span></p> <p><span> </span></p> <p><strong><span>2. Data processing</span></strong></p> <p><span>T</span><span>he GAMIT </span><span>package </span><span>(</span><span>Herring et al., 2015</span><span>a</span><span>) </span><span>was employed </span><span>to process</span><span> the </span><span>double-differenced carrier phase observations</span><span>, and daily </span><span>loosely constrained solutions</span><span> were obtained</span><span>. </span><span>The primary geophysical models and parameters used in the processing, such as</span><span> the </span><span>FES2004 tidal loading model, GPT2 global pressure and temperature model (</span><span>Lagler et al., 2013</span><span>), and VMF1 </span><span>mapping</span><span> function (</span><span>Boehm et al., 2006</span><span>),</span><span> are</span><span> the</span><span> same </span><span>as </span><span>those in </span><span>Hao et al. (2021)</span><span>. Instead of incorporating global daily solutions provided by the IGS analysis centers, we also processed data from ~</span><span>70 evenly distributed global International Terrestrial Reference Frame (ITRF) core tracking </span><span>GNSS sites</span><span> using the GAMIT package with the same models. </span><span>We estimated</span><span> daily coordinates and uncertainties by constraining the daily regional solutions with global solutions, and the daily free network solutions were transformed into </span><span>the </span><span>ITRF2014 (</span><span>Altamimi et al., 2017</span><span>) </span><span>reference frame by utilizing</span><span> the GLOBK package</span><span> (</span><span>Herring et al., 2015</span><span>b</span><span>)</span><span>.</span><span> For campaign GNSS sites, the weighted least-squares adjustment was used to solve the linear velocity with respect to the ITRF2014.</span></p> <p><span>To analyze the differential crustal motion between blocks, we selected the stable Ordos block as the regional reference frame and transformed the GNSS velocity field referenced to the ITRF2014 into the Ordos-fixed frame through Euler rotation. The absolute Euler pole of the Ordos block is located at 75.083°N ± 0.850°</span><span> and</span><span> 139.692°W ± 3.701°, with an angular rotation rate of 0.352 ± 0.</span><span>006°/Ma </span><span>(</span><span>Hao et al., 2021</span><span>).</span></p> <p><span> </span></p> <p><strong><span>References</span></strong></p> <p><span>Altamimi, Z., Métivier, L, Rebischung, P., Rouby, H., Collilieux, X., 2017. ITRF2014 plate motion model.Geophys. J. Int. 209:1906–1912</span></p> <p><span>Boehm, J., Werl, B., and Schuh, H. (2006). Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data. Journal of Geophysical Research, 111, B0240</span><span><a href="https://doi.org/10.1029/2005JB003629"><span>. doi:10.1029/2005JB003629</span></a></span><span>.</span></p> <p><span>Hao, M., Wang, Q., Zhang, P., Li, Z., Li, Y., Zhuang, W., 2021.“Frame wobbling” causing crustal deformation around the Ordos block. Geophysical Research Letters 48, e2020GL091008. https://doi.org/10.1029/2020GL091008.</span></p> <p><span>Herring, T.A., King, R.W., McClusky, S.C., 2015b.GAMIT reference manual, global Kalman filter VLBI and GPS analysis program, Release 10.6.Massachusetts Institute of Technology, Cambridge.</span></p> <p><span>Herring, T.A., King, R.W.,McClusky, S.C., 2015a.GAMIT reference manual, GPS analysis at MIT, Release 10.6.Massachusetts Institute of Technology, Cambridge.</span></p> <p><span>Lagler, K., Schindelegger, M., Böhm, J., Kr</span><span>á</span><span>sn</span><span>á</span><span>, H., and Nilsson, T. (2013). GPT2: empirical slant delay model for radio space geodetic techniques. GeophysicalResearchLetters, 40, 1069-1073. doi: 10.1002/grl.50288.</span></p>
Airglow Imager and GNSS-TEC Data on 09 June 2021
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Inversion of GNSS-based 3D Displacement for Daily Terrestrial Water Storage Changes under the 2023 Beijing-Tianjin-Hebei Heavy Rain in China
<p>The data and code for "Inversion of GNSS-based 3D Displacement for Daily TerrestriaI Water Storage Changes under the 2023 Beijing-Tianjin-Hebei Heavy Rain in China".</p> <p>Including:</p> <p>I. the GNSS and water level dataset;</p> <p>II, the codes for Inversion of GNSS for mass loads.</p>
Identification of Three-Dimensional Landslide Movement Based on GNSS Measurement and Geological Properties to Improve Disaster Mitigation Response
<p>This material has presented on 2nd International Conference on Advanced Research in Engineering and Technology in October 25, 2023.</p>
Real-time oceanic PWV sensing using BeiDou-3 PPP-B2b and low-cost GNSS devices
<div>This dataset consists of two parts, GNSSDATA and RESULT, which were utilized in the manuscript: "Real-time oceanic PWV sensing using BeiDou-3 PPP-B2b and low-cost GNSS devices."</div> <div><strong>GNSSDATA:</strong> This dataset contains shipborne BeiDou/GNSS data spanning four days, from 00:00 on September 21 to 00:00 on September 25, 2023. The data was collected using a low-cost GNSS receiver, the Septentrio mosaic-X5, and is stored in Septentrio Binary Format (SBF). The raw BeiDou/GNSS observations, PPP-B2b corrections (orbits/clocks/code bias), and broadcast ephemeris can be decoded from the SBF format using Septentrio RxTools.</div> <div><strong>RESULT:</strong> This dataset includes the PPP-B2b-derived zenith tropospheric delay (ZTD) solutions obtained from the above GNSS data, based on the five schemes designed in the manuscript.</div>
Enhancing Regional Quasi-Geoid Refinement Precision: An Analytical Approach Employing ADS80 Tri-linear Array Stereoscopic Imageryand GNSS Gravity-Potential Leveling
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GNSS Signal samples in the L2 band
<p>GNSS signals captured in the L2 band.</p> <p>Format: Baseband</p> <p>Data Type: Interleaved short ( I & Q samples, 16-bit signed integer)</p> <p>Sampling frequency: 3.125 MSps</p> <p>Signal grabber: USRP X300</p> <p>Date: February 12, 2018.</p>
GNSS Signal samples in the L2 band
<p>Signal samples in the L2 band (centered at 1227.60 MHz).</p> <p>Sampling frequency: 3 MSps. No Intermediate Frequency.</p> <p>The sample format is `ibyte`: Interleaved (I&Q) stream of samples of type signed integer, 8-bit two’s complement number ranging from -128 to 127.</p>
GNSS and Wind Speed Dataset from North Sea Wave Glider 2016 Deployment
<p>5 Hz GNSS RINEX and 10 min wind speed data collected on-board an SV2 Wave Glider in the North Sea from 28 July to 10 August 2016 used in Penna et al, “Sea Surface Height Measurement Using a GNSS Wave Glider”, submitted to Geophysical Research Letters.</p> <p> </p>
GATEMAN project -- Wide-bandwidth, high-precision GNSS and jammer raw data
<p>This dataset contains high quality GNSS and jammer raw data generated during the in-lab validation activities of jamming detection and localization performed in the frame of the GATEMAN project. These files are grouped for each type of validation scenario defined. The scenarios are combinations of three different GNSS and three different jamming signals.</p> <p><strong>Content:</strong></p> <p>The archive contains a folder for each validation scenario. Each folder contains two files. One contains the GNSS data and the second file contains jamming data. A function to read the data with GNU Octave/Matlab is also included.</p> <p>├── GALE1+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GALE1+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GALE1+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GALE1@20MSps.bin<br> ├── GPSL1+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL1+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL1+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GPSL1@20MSps.bin<br> ├── GPSL5+AMtone<br> │ ├── AMtone@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> ├── GPSL5+Chirp10MHz<br> │ ├── Chirp10MHz@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> ├── GPSL5+Chirp20MHz<br> │ ├── Chirp20MHz@20MSps.bin<br> │ └── GPSL5@20MSps.bin<br> └── readBinData.m</p> <p> </p> <p><strong>Data format:</strong></p> <p>Each file stores the received baseband samples as an array of complex, 16-bit signed integer data (range -32,768 to 32,767) of the corresponding signal. The data is stored in Big-endian, network order format, i.e. the most-significant byte occupies the lowest memory address. The real and imaginary components of the data correspond to the in-phase (I) and quadrature-phase (Q) data, respectively. I and Q-samples are interleaved [I, Q, I, Q, ...] in the array.</p> <p> </p> <p><strong>Data:</strong></p> <p>The recorded data of each validation scenario consists of two files, one containing the GNSS signal (L1, L5 or E1 band), the other one containing the jamming signal (tone, chirp 10 & 20 MHz bandwidth). The RF GNSS signal was generated with a GNSS signal generator, it contains only a single spreading sequence. The RF jamming signal was generated with a Vector Signal Transceiver. Both signals of a scenario were recorded synchronously with an USRP at an I\Q rate of 20 MS/s.</p> <p>GNSS signals:</p> <ul> <li>Startime: 30.05.2018 at 12:00 (approximately)</li> <li>Latitude: N 50 deg, 50.4864 min</li> <li>Longitude: E 4 deg, 21.3499 min</li> <li>Altitude: 50m</li> <li>Trajectory: Static</li> <li>Ephemeris file: brdc1500.18.n</li> </ul> <p><br> GNSS band PRN Elevation (deg) Azimuth (deg) Power (dBm)<br> GPS L1 4 85 187 -70<br> GPS L5 4 85 193 -70<br> Galileo E1 E14 66 274 -68.5</p> <p>Jamming signals:</p> <ul> <li>The tone is simple a sinosoidal waveform in the centre of the GNSS bands.</li> <li>The chirps are linear frequency modulated waveforms (sawtooth) in the centre of the GNSS bands with sweep range of 10 MHz and 20 MHz and sweep period of 8.64 µs.</li> </ul> <p> </p> <p> </p> <p>The data uploaded here are a truncated samples. Longer samples of data are available upon request.</p>
GNSS time series used for manuscript 2019JB017614R
<p>This dataset includes the raw time series used for deriving the GNSS velocity solution in manuscript 2019JB017614R submitted to Journal of Geophysical Research: Solid Earth (Strain Accommodation in the Daliangshan Mountain area, Southeastern Margin of the Tibetan Plateau).</p>
GNSS observations along the Hellenic Arc
<p>Dataset includes available GNSS observation along the Hellenic Subdction Margin.</p>
Quality Assessment of YUNYAO GNSS-RO Refractivity Data in the Neutral Atmosphere
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RINEX files from low-cost and geodetic-grade GNSS receivers, Wrocław, Poland; Sofia, Bulgaria; March-April, 2024 with Galileo HAS files
<p>Daily RINEX files with multi-GNSS (GPS, GLONASS, Galileo,BeiDou) observations at 30 sec. interval obtained with two low-cost GNSS receiver u-blox ZED-F9P in Wrocław, Poland (PL01), Sofia, Bulgaria (BG01) and two geodetic-grade receivers in Wrocław, Poland (WROC) and Sofia, Bulgaria (SUZF). Time period: 29.03.2024 - 24.04.2024. Galileo HAS files are also shared.</p>
An integrated GNSS velocity field in the Pamir, Central Asia
<p>GPS velocity field in the Pamir region in the Eurasian-fixed frame compiled from our latest results and previous studies. Site with upperscript c is a continuous GPS staiton.</p>
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