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dc.contributor.authorWinter, Hanno
dc.date.accessioned2020-11-27T07:24:17Z
dc.date.available2020-11-27T07:24:17Z
dc.date.issued2020-12-10
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2529
dc.identifier.urihttps://doi.org/10.25534/tudatalib-359
dc.description<p><strong>Key facts</strong></p> <ul> <li><strong>Fields of application:</strong><br /> railway positioning, sensor fusion, sensor models</li> <li><strong>Available data:</strong><br /> 1x GNSS, 1x IMU</li> <li><strong>Rail-track characteristics:</strong><br /> &asymp;870 km (on convetional lines)</li> <li><strong>Available reference data:</strong><br /> Open GNSS/IMU EKF-fusion solution (loosely coupled)</li> <li><strong>Structure:</strong><br /> This data set follows the data sharing principles of the LRT (localization reference train) initiative that are available at <a href="https://lrt-initiative.org/2020_05_28_lrtdatasetguidelines_v1_2/">lrt-initiative.org</a>.</li> </ul> <p><strong>About</strong></p> <p>This data set can be used for rail vehicle positioning experiments. It contains measurements of an 6-DOF IMU and a GNSS receiver. The senors were mounted on a regular rail vehicle during a trip from Chemnitz (Germany, Saxony) to Neuffen (Germany, Baden-Württemberg) and back.</p> <p>The recorded data have been pre-processed to have common time and coordinate frames. Furthermore, a simple loosely coupled GNSS/IMU positioning solution is provided which can be used as a baseline for more advanced fusion approaches.</p> <p>All MATLAB scripts used to process the raw data and to calculate the GNSS/IMU positioning solution are provided within the data set. </p> <p>The data can be used as a starting point for own work. Special features of this data set are its overall length (870km, 16hrs) with continuous journey sections of over 1h and its test-track (conventional line).</p> <p><strong>Similar data sets</strong></p> <ul> <li><a href="https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2292.2" target="_blank">https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2292.2</a></li> <li><a href="https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2530" target="_blank">https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2530</a></li> </ul> <style type="text/css"> <!-- .rvpds_tab { margin-left: 40px; } --> </style> <p><strong>BibTex</strong></p> <p>@Misc{WinterRailDataSetMarch2019,<br/> <span class="rvpds_tab">title = {Rail Vehicle Positioning Data Set: Lucy, March 2019},</span><br/> <span class="rvpds_tab">author = {Winter, Hanno},</span><br/> <span class="rvpds_tab">doi = {10.25534/tudatalib-359},</span><br/> <span class="rvpds_tab">publisher = {Technische Universität Darmstadt},</span><br/> <span class="rvpds_tab">year = {2020},</span><br/> } </p>en_US
dc.language.isoenen_US
dc.rightsCreative Commons Attribution 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectRailwayen_US
dc.subjectPositioningen_US
dc.subjectData Seten_US
dc.subjectTrainen_US
dc.subjectLocalizationen_US
dc.subjectGNSSen_US
dc.subjectIMUen_US
dc.subjectSensor Fusionen_US
dc.subject.classification407-04 Verkehrs- und Transportsysteme, Intelligenter und automatisierter Verkehr
dc.subject.ddc380
dc.titleRail Vehicle Positioning Data Set: Lucy, March 2019en_US
dc.typeDataseten_US
dc.typeSoftwareen_US
dc.description.versioninitial versionen_US
tud.history.classificationVersion=2016-2020;407-04 Verkehrs- und Transportsysteme, Logistik, Intelligenter und automatisierter Verkehr;


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Creative Commons Attribution 4.0
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