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Proceedings ArticleDOI

Semi-autonomous indoor positioning using MEMS-based inertial measurement units and building information

TLDR
A novel combination of methods is proposed to increase the distance between positions where absolute repositioning is still mandatory, and the prototype of a self-contained indoor positioning system is presented.
Abstract
State-of-the-art indoor positioning systems are based on short-range wireless technologies such as ultra-wideband (UWB) and wireless local area network (WLAN). Additional information produced by a low-cost inertial measurement unit (IMU) or selected from low-grade floor plans is frequently used to improve the positioning accuracy. Therefore absolute and relative positioning systems (e.g. WLAN and IMU) are typically integrated using a Kalman filter (KF) or a particle filter (PF). In this case, all the buildings have to be equipped with a large number of transmitters and receivers which may render inoperable during emergency situations and induce substantial costs both in terms of setup and maintenance. Hence, in this paper we present and assess the prototype of a self-contained indoor positioning system. Our prototype consists of a micro-electro-mechanical system- (MEMS) based IMU and a mobile computer which includes a database with characteristic building information. A novel combination of methods is proposed to increase the distance between positions where absolute repositioning is still mandatory.

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Citations
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Journal ArticleDOI

Distributed Indoor Positioning System With Inertial Measurements and Map Matching

TL;DR: A distributed system for personal positioning based on inertial sensors that consists of an inertial measurement unit connected to a radio carried by a person and the server connected to another radio, which leads to long operation time as power consumption also remains very low.
Journal ArticleDOI

Algorithms for automated generation of navigation models from building information models to support indoor map-matching

TL;DR: Algorithms for automated generation of three different types of navigation models, namely, centerline-based network, metric-based and grid-based Navigation models, for map-matching of indoor positioning data are presented.
Journal ArticleDOI

Analysis of Three Indoor Localization Technologies for Supporting Operations and Maintenance Field Tasks

TL;DR: In this paper, the authors describe the process of locating building components that need to be worked on during maintenance tasks, which is critical for timely repair of the component and mitigation of the damage.
Proceedings ArticleDOI

A study on indoor pedestrian localization algorithms with foot-mounted sensors

TL;DR: The work presents a foot-mounted sensor system for a combined indoor/outdoor pedestrian localization based on a zero-velocity update scheme formulated as an Extended or Unscented Kalman filter with quaternion orientation representation and employs a custom low-cost sensor unit.
Proceedings ArticleDOI

Context-adaptive algorithms to improve indoor positioning with inertial sensors

TL;DR: Two context-adaptive algorithms to improve indoor positioning with inertial sensors are presented and the achieved results are discussed.
References
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Journal ArticleDOI

Some map matching algorithms for personal navigation assistants

TL;DR: This paper considers map matching algorithms that can be used to reconcile inaccurate locational data with an inaccurate map/network.
Journal ArticleDOI

Inertial sensor technology trends

TL;DR: In this paper, the authors present an overview of how inertial sensor technology is applied in current applications and how it is expected to be applied in near and far-term applications, namely interferometric fiber-optic gyros, micro-mechanical gyros and accelerometers and micro-optical sensors.

An Introduction to Map Matching for Personal Navigation Assistants

TL;DR: This paper examines Personal Navigation Assistants (PNAs) and explores map-matching algorithms that can be used to reconcile inaccurate locational data with an inaccurate map/network.
Proceedings ArticleDOI

WLAN-Based Pedestrian Tracking Using Particle Filters and Low-Cost MEMS Sensors

TL;DR: A pedestrian tracking framework based on particle filters is proposed, which extends the typical WLAN-based indoor positioning systems by integrating low-cost MEMS accelerometer and map information.
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