Abstract
Fingerprint-based positioning in Wi-Fi environment has caught much attention recently. One key issue is about the radio map construction, which generally requires significant effort to collect enough Wi-Fi Received Signal Strength (RSS) measurements. Based on the observation that the Micro Electromechanical System (MEMS) can automatically calibrate the target locations without complex equipment, we propose an efficient radio map construction method based on the technology of multi-sensor. Different from the conventional methods, the proposed one first relies on the gait detection approach and quaternion-based extend Kalman filter algorithm to estimate the velocity and heading of the target. Second, the Pedestrian Dead Reckoning (PDR) algorithm is used to calculate the current location of the target in a real-time manner, and meanwhile the data from Wi-Fi module are collected to generate the fingerprint database. The experimental results show that the proposed method is effective in positioning accuracy and efficient by saving the time and energy.
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Acknowledgements
The authors wish to thank the reviewers for the careful review and valuable suggestions. This work was supported in part by the Program for Changjiang Scholars and Innovative Research Team in University (IRT1299), National Natural Science Foundation of China (61301126), Special Fund of Chongqing Key Laboratory (CSTC), and Fundamental and Frontier Research Project of Chongqing (cstc2015jcyjBX0065).
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Tian, Z., Wu, Z., Zhou, M., Li, Z., Jin, Y. (2018). A Novel Method to Generate Wi-Fi Fingerprint Database Based on MEMS. In: Liang, Q., Mu, J., Wang, W., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2016. Lecture Notes in Electrical Engineering, vol 423. Springer, Singapore. https://doi.org/10.1007/978-981-10-3229-5_3
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DOI: https://doi.org/10.1007/978-981-10-3229-5_3
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