Abstract
As the rapid development of mobile Internet, many location-based services (LBS) have emerged for commercial cooperation, entertainment, security, and so forth. All of these require accurate and real time positioning of mobile devices with seamless indoor-outdoor transition in high dense urban regions. While satisfactory outdoor location services are achieved based on the global navigation satellite system (GNSS) technology, a really ubiquitous location system for both indoor and outdoor scenarios is not yet available. To cope with this challenge, we propose a hybrid location system, which makes the best of WIFI reference signal strength index (RSSI) fingerprinting technique for indoor positioning, traditional GNSS for the outdoor positioning, and pedestrian dead reckoning (PDR) technology for supplement. An environment-adaptive positioning handover module is proposed to perform positioning technology switching as environment changes. Moreover, a novel algorithm based on continuous hidden Markov model (CHMM) is proposed for the navigation in the indoor regions. Extensive tests for the seamless system proposed have been performed with satisfactory results and effectiveness.
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References
Liu, H., Darabi, H., Banerjee, P., Liu, J.: Survey of wireless indoor positioning techniques and systems. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 37, 1067–1080 (2007)
Fang, S.-H., Lin, T.-N., Lin, K.-C.: A novel algorithm for multipath fingerprinting in indoor WLAN environments. IEEE Trans. Wirel. Commun. 7, 3579–3588 (2008)
Luo, Y., Law, C.L.: Indoor positioning using UWB-IR signals in the presence of dense multipath with path overlapping. IEEE Trans. Wirel. Commun. 11, 3734–3743 (2012)
Alshamaa, D., Mourad-Chehade, F., Honeine, P.: Tracking of mobile sensors using belief functions in indoor wireless networks. IEEE Sens. J. 18, 310–319 (2018)
Gan, X., Yu, B., Heng, Z., Huang, L., Li, Y.: Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS), pp. 1–7 (2018)
Mozamir, M.S., Bakar, R.B.A., Din, W.I.S.W.: Indoor localization estimation techniques in wireless sensor network: a review. In: 2018 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS), pp. 148–154 (2018)
Yuan, Y., Melching, C., Yuana, Y., et al.: Multi-device fusion for enhanced contextual awareness of localization in indoor environments. IEEE Access 6, 7422–7431 (2018)
Wang, C., Luo, J., Zheng, Y.: Optimal target tracking based on dynamic fingerprint in indoor wireless network. IEEE Access 6, 77226–77239 (2018)
Zundt, M., Ippy, P., Laqua, B., Eberspächer, J.: LACBA - a location – aware community – based architecture for realizing seamless adaptive location-based service. In: 12th European Enabling Technologies for Wireless Multimedia Communications, pp. 1–7 (2006)
Kruppa, M.: Emergency indoor and outdoor user localization. In: Wichert, R., Eberhardt, B. (eds.) Ambient Assisted Living, pp. 239–256. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-18167-2_17
Di Flora, C., Ficco, M., Russo, S., Vechio, V.: Indoor and outdoor location based services for portable wireless devices. In: IEEE International Conference on Distributed Computing Systems Workshops, pp. 244–250 (2005)
Sakamoto, Y., Ebinuma, T., Fujii, K., Sugano, S.: GPS-compatible indoor-positioning methods for indoor-outdoor seamless robot navigation. In: Advanced Robotics and its Social Impacts (ARSO), pp. 95–100 (2012)
Fernadez-Madrigal, J.A., Cruz-Martin, E., Gonzalez, J., Galindo, C., Blabco, J.L.: Application of UWB and GPS technologies for vehicle localization in combined indoor-outdoor environments. In: International Symposium on Signal Processing and Its Applications, pp. 1–4 (2007)
Kuusniemi, H., Chen, L., Ruotsalainen, L., Pei, L., Chen, Y., Chen, R.: Multi-sensor multi-network seamless positioning with visual aiding. In: International Conference on Localization and GNSS, pp. 146–151 (2011)
Nord, J., Synnes, K., Parnes, P.: An architecture for location aware applications. In: Proceedings of the 35th Hawaii International Conference on System Science (2002)
Peng, J., Zhu, M., Zhang, K.: New algorithms based on sigma point Kalman filter technique for multi-sensor integrated RFID indoor/outdoor positioning. In: Indoor Positioning and Indoor Navigation (IPIN), pp. 21–25 (2011)
Johannes, L., Degener, J., Niemeier, W.: Set-up of a combined indoor and outdoor positioning solution and experimental results. In: Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6 (2010)
Yan, M., Yubin, X., Xiuwan, C.: Wireless local area network assisted GPS in seamless positioning. In: Computer Science Electronics Engineering (ICCSEE), pp. 612–615 (2012)
Khan, M.S.Z., Tan, C.-W., Silvadorai, T., Ramadass, S.: Novel algorithm to ensure smooth and unobtrusive handover among positioning systems. In: Information Retrieval & Knowledge Management (CAMP), pp. 229–234 (2012)
Hansen, R., Wind, R., Jensen, C.S., Thomsen, B.: Seamless indoor/outdoor positioning handover for location-based services in StreamSpin. In: Proceedings of the 10th International Conference on Mobile Data Management Systems, Services and Middleware, pp. 267–272 (2009)
Ran, L., Helal, S., Moore, S.: Drishti: an integrated indoor/outdoor blind navigation system and service. In: Proceeding of the Second IEEE Annual Conference on Pervasive Computing and Communications, pp. 23–30 (2004)
Bancroft, J.B., Garrett, D., Lachapelle, G.: Activity and environment classification using foot mounted navigation sensors. In: Indoor Positioning and Indoor Navigation (IPIN), pp. 1–6 (2010)
Zhou, P., Zheng, Y., Li, Z., Li, M., Shen, G.: IODetector: a generic service for indoor outdoor detection, SenSys 2012, Toronto, Canada (2012)
Bullock, J.B., Chowdhary, M., Rubin, D., Leimer, D., Turetzky, G., Jarvis, M.: Continuous indoor positioning using GNSS, Wi-Fi and MEMS dead reckoning. In: ION GNSS, pp. 2408–2416 (2012)
Rabiner, L.R.: A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77, 257–286 (1989)
Viterbi, A.: Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans. Inf. Theory 13, 260–269 (1967)
Kealy, A., Roberts, G.: Evaluating the performance of low cost MEMS inertial sensors for seamless indoor/outdoor navigation. In: Position Location and Navigation Symposium (PLANS), ION, pp. 157–167 (2010)
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Du, Y., Yang, D. (2019). Seamless Positioning and Navigation System Based on GNSS, WIFI and PDR for Mobile Devices. In: Han, S., Ye, L., Meng, W. (eds) Artificial Intelligence for Communications and Networks. AICON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 286. Springer, Cham. https://doi.org/10.1007/978-3-030-22968-9_48
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DOI: https://doi.org/10.1007/978-3-030-22968-9_48
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