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Updated: Feb 5, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
Published on: February 25, 2013
Pekka Peltola1, Jialin Xiao2, Terry Moore3
1Centre for Automation and Robotics (CAR), Spanish Council for Scientific Research (CSIC-UPM), Ctra. de Campo Real km 0,200, Arganda del Rey, 28500 Madrid, Spain. pekka.peltola@csic.es.
This study detects Global Navigation Satellite System (GNSS) trajectory anomalies in urban areas by comparing GNSS data with trusted pedestrian dead reckoning. The Hausdorff distance and accumulated distance difference methods proved most effective for anomaly detection.
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