iBILL: Using iBeacon and Inertial Sensors for Accurate Indoor Localization in Large Open Areas
Abstract
As a key technology that is widely adopted in location-based services (LBS), indoor localization has received considerable attention in both research and industrial areas. Despite the huge efforts made for localization using smartphone inertial sensors, its performance is still unsatisfactory in large open areas, such as halls, supermarkets, and museums, due to accumulated errors arising from the uncertainty of users' mobility and fluctuations of magnetic field. Regarding that, this paper presents iBILL, an indoor localization approach that jointly uses iBeacon and inertial sensors in large open areas. With users' real-time locations estimated by inertial sensors through an improved particle filter, we revise the algorithm of augmented particle filter to cope with fluctuations of magnetic field. When users enter vicinity of iBeacon devices clusters, their locations are accurately determined based on received signal strength of iBeacon devices, and accumulated errors can, therefore, be corrected. Proposed by Apple Inc. for developing LBS market, iBeacon is a type of Bluetooth low energy, and we characterize both the advantages and limitations of localization when it is utilized. Moreover, with the help of iBeacon devices, we also provide solutions of two localization problems that have long remained tough due to the increasingly large computational overhead and arbitrarily placed smartphones. Through extensive experiments in the library on our campus, we demonstrate that iBILL exhibits 90% errors within 3.5 m in large open areas.
Additional Information
© 2017 IEEE. Received June 10, 2017, accepted June 27, 2017, date of publication July 17, 2017, date of current version August 14, 2017. This work was supported in part by NSF China under Grant 61532012, Grant 61325012, Grant 61271219, Grant 61521062, Grant 61602303, Grant 61572319, and Grant 91438115, and in part by the China Postdoctoral Science Foundation.Attached Files
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Additional details
- Eprint ID
- 79217
- Resolver ID
- CaltechAUTHORS:20170719-170603229
- 61532012
- National Natural Science Foundation of China
- 61325012
- National Natural Science Foundation of China
- 61271219
- National Natural Science Foundation of China
- 61521062
- National Natural Science Foundation of China
- 61602303
- National Natural Science Foundation of China
- 61572319
- National Natural Science Foundation of China
- 91438115
- National Natural Science Foundation of China
- China Postdoctoral Science Foundation
- Created
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2017-07-20Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field