An Optimal Data Fusion Approach for Precise Position Estimation of Smartphone User: An Optimal Data Fusion Approach for Precise Position Estimation of Smartphone User

Harun Jamil

Authors

Harun Jamil Department of Electronic Engineering, Jeju National University, Jeju-si, Jeju-do, Republic of Korea, 63243.

Keywords:

Data Fusion, BLE, PDR, Indoor Positioning, artificial intelligence, ANN, Particle Filter

Abstract

This paper proposes an optimal data fusion approach for precise position estimation of smartphone users in challenging environments, combining BLE-based indoor position estimation and PDR using smartphone sensors. The approach utilizes RSSI values from nearby BLE beacons for BLE-based estimations and employs PDR with an accelerometer, magnetometer, and gyrometer for position orientation. These observations are then fed into an ANN for accurate position prediction, and Particle Filter is used for probabilistic pedestrian position prediction. Experimental results demonstrate improved accuracy compared to individual techniques, making the approach robust for accurate smartphone user positioning in challenging environments.

Author Biography

Harun Jamil, Department of Electronic Engineering, Jeju National University, Jeju-si, Jeju-do, Republic of Korea, 63243.

Harun Jamil received the B.Sc. degree in electronic engineering from the Capital University of Science and Technology, Islamabad, Pakistan, and the M.S.E.E. degree in electrical engineering from Air University, Islamabad, in 2019. He is currently pursuing the Ph.D. degree with the Department of Electronic Engineering, Jeju National University, Jeju-Si, South Korea.,His research interests include indoor localization, data fusion techniques, nanogrids, energy optimization, and prediction

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An Optimal Data Fusion Approach for Precise Position Estimation of Smartphone User