A Survey of Indoor Inertial Positioning Systems for Pedestrians

By Robert K. Harle. IEEE Communications Surveys and Tutorials, 2013

842 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/f873082d86155bfaf4552e5b93aff18f5158cf9d

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In Biomedical Engineering

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Citations in the corpus

A Survey of Wearable Devices and Challenges (2017, background): “[20] briefly surveyed the use of wearables as sensing units and similarly Harle [21] surveyed the use of wearables in indoor positioning applications.”
Location Fingerprinting With Bluetooth Low Energy Beacons (2015, background): “fingerprints with other sources to form hybrid systems, many of which are based on the idea of Simultaneous Localization and Mapping (SLAM) [10], [16] being applied to pedestrian dead reckoning [13].”
Non-GPS Positioning Systems (2017, methodology): “Indoor localization can have various applications such as safety, security, resource efficiency, automatic resource routing, location based marketing, visitor navigation, and so on [41].”
A Survey of Selected Indoor Positioning Methods for Smartphones (2017, methodology): “The template can be previously recorded walking data from the same person [73].”
Learning Switching Models for Abnormality Detection for Autonomous Driving (2018, background): “State estimation is important for motion prediction [1], [2], tracking [3–5], identification”
IONet: Learning to Cure the Curse of Drift in Inertial Odometry (2018, methodology): “However, dynamic step estimation is heavily inﬂuenced by sensor noise, user’s walking habits and phone attachment changes, causing unavoidable errors to the entire system (Brajdic and Harle 2013).”
Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion (2017, methodology): “[25] provide a technical review of the issues arising and methods used in IMU-based pedestrian localization.”
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, background): “Step counting is currently a major approach to capture the movement and walking path of pedestrians [91].”
Using Inertial Sensors for Position and Orientation Estimation (2017, neutral): “6 1.3 Tutorial content and its outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7”
A Survey of Enabling Technologies for Network Localization, Tracking, and Navigation (2018, background): “Loop closure refers to the process of identifying that the user has returned to a physical location, which was visited previously while surveying, and enables resetting the PDR tracking algorithm to avoid inertial sensor drift; a survey of PDR systems based on inertial sensors can be found in [257].”
Modern WLAN Fingerprinting Indoor Positioning Methods and Deployment Challenges (2016, background): “ing the user’s motion such as counting user’s steps, inertial navigations, and heading directions [126].”
Application of Local Differential Privacy to Collection of Indoor Positioning Data (2018, background): “In order to make such indoor location-based service possible, it is essential to accurately estimate the indoor position of a user; thus, related technologies have been actively studied over the last decade [13], [14], [19], [26].”
Walk detection and step counting on unconstrained smartphones (2013, background): “Similarly, many trials in the PDR field involve asking a small number of users to walk ‘naturally’ for a few minutes in an area clear of obstructions.”