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Título: | GNSS Trajectory Anomaly Detection Using Similarity Comparison Methods for Pedestrian Navigation |
Autor: | Peltola, Pekka; Xiao, Jialin; Moore, Terry; Jiménez Ruiz, Antonio R. CSIC ORCID ; Seco Granja, Fernando CSIC ORCID | Palabras clave: | Similarity GNSS trajectory Pedestrian dead reckoning Multipath Anomaly detection |
Fecha de publicación: | 19-sep-2018 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Sensors 18(9): 3165 (2018) | Resumen: | The urban setting is a challenging environment for GNSS receivers. Multipath and other anomalies typically increase the positioning error of the receiver. Moreover, the error estimate of the position is often unreliable. In this study, we detect GNSS trajectory anomalies by using similarity comparison methods between a pedestrian dead reckoning trajectory, recorded using a foot-mounted inertial measurement unit, and the corresponding GNSS trajectory. During a normal walk, the foot-mounted inertial dead reckoning setup is trustworthy up to a few tens of meters. Thus, the differing GNSS trajectory can be detected using form similarity comparison methods. Of the eight tested methods, the Hausdorff distance (HD) and the accumulated distance difference (ADD) give slightly more consistent detection results compared to the rest. | Versión del editor: | https://doi.org/10.3390/s18093165 | URI: | http://hdl.handle.net/10261/169993 | DOI: | 10.3390/s18093165 | ISSN: | 1424-8220 |
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sensors-18-03165.pdf | 4,83 MB | Adobe PDF | Visualizar/Abrir |
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