Trusted K Nearest Bayesian Estimation for Indoor Positioning System
| Autor: | Hui-Seon Gang, Rohan Kumar Yadav, Jae-Young Pyun, Bimal Bhattarai |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
fuzzy-logic system
General Computer Science Positioning system Computer science Real-time computing 02 engineering and technology 01 natural sciences Fuzzy logic law.invention Bluetooth low energy (BLE) Bluetooth Indoor positioning system K-nearest neighbor (KNN) Inertial measurement unit law Dead reckoning General Materials Science Bayes estimator 010401 analytical chemistry General Engineering indoor positioning Kalman filter fingerprints Bayesian estimation 021001 nanoscience & nanotechnology 0104 chemical sciences lcsh:Electrical engineering. Electronics. Nuclear engineering 0210 nano-technology lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 7, Pp 51484-51498 (2019) |
| ISSN: | 2169-3536 |
| Popis: | Indoor positioning systems have received increasing attention because of their wide range of indoor applications. However, the positioning system generally suffers from a large error in localization and has low solidity. The main approaches widely used for indoor localization are based on the inertial measurement unit (IMU), Bluetooth, Wi-Fi, and ultra-wideband. The major problem with Bluetooth-based fingerprinting is the inconsistency of the radio signal strength, and the IMU-based localization has a drift error that increases with time. To compensate for these drawbacks, in the present study, a novel positioning system with IMU sensors and Bluetooth low energy (BLE) beacon for a smartphone are introduced. The proposed trusted K nearest Bayesian estimation (TKBE) integrates BLE beacon and pedestrian dead reckoning positionings. The BLE-based positioning, using both the K-nearest neighbor (KNN) and Bayesian estimation, increases the accuracy by 25% compared with the existing KNN-based positioning, and the proposed fuzzy logic-based Kalman filter increases the accuracy by an additional 15%. The overall performance of TKBE has an error of |
| Databáze: | OpenAIRE |
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