This paper deals with navigation of mobile device in outdoor and indoor environment by only navigation system or application. In the paper, the navigation system is proposed in the light of seamless navigation service. Main parts of the system from positioning point of view are based on GPS and WifiLOC system. WifiLOC is an indoor positioning system based on Wi-Fi technology. The proposal of the system will be described in detail. The system is implemented at the University of Zilina as a pilot, noncommercial project; therefore it is called University Mobile Navigation System (UMNS). The navigation system can be characterized as real-time system, that is, the system operations cannot be significantly delayed. Since delay of the system depends significantly on communication platform used for map information downloading or communication with the localization server. We decided to investigate an impact of the used communication platform on the time needs for some of the functions implemented in navigation system. Measurements were performed in the real-world application. Next experiment is focused on testing of the accuracy of used indoor positioning system. Outdoor positioning accuracy is not tested because GPS is utilized in outdoor, and this system was already exhaustively investigated. 1. Introduction In past few years, high number of navigation systems for mobile devices was successfully developed. Most of these systems can be used in outdoor environment, where position of the mobile device is estimated using satellite systems like GPS (Global Positioning System) or GLONASS (Global Navigation Satellite System). Generally, these systems are mainly used in transport applications, to find shortest path to the given destination point in the field of navigation, but can also be used for pedestrian navigation or navigation of the blind people [1–4]. Similar situation is in the indoor environment. Many navigation systems were developed also for this environment and they are mostly used for navigation in large buildings [5–7]. Most of these systems using radio signal positioning to achieve position estimate, which is important for the navigation applications [7]. It is also possible to use a high-sensitivity GPS receivers or GPS pseudolites in the indoor environment, but this solution is still quite expensive [8, 9]. The largest number of indoor navigation systems is based on the Wi-Fi technology and use fingerprinting positioning to estimate position of mobile device [10]. In this paper, we will propose navigation system for mobile device, which can be used
References
[1]
S. Jung and W. Woo, “UbiTrack: infrared-based user Tracking System for indoor environment,” in Proceedings of the International Conferece on Artificial Reality and Telexisitence (ICAT '04), pp. 181–184, Coex, Korea, 2004.
[2]
H. Makino, I. Ishii, and M. Nakashizuka, “Development of navigation system for the blind using GPS and mobile phone combination, engineering in medicine and biology society,” in Proceedings of the 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, vol. 2, pp. 506–507, November 1996.
[3]
M. Hao and S. Xi, “Research of TETRA terminal navigation and location system based on GPS/GIS,” Instrument Standardization and Metrology, no. 5, pp. 18–19, 2006.
[4]
G. Hong-wei, B. Xiang, and Q. I. Qin, “On positioning and navigation of mobile-phone based on gpsOne,” Microcomputer Application Technology, no. 69, pp. 34–37, 2007.
[5]
O. Cruz, E. Ramos, and M. Ramirez, “3D indoor location and navigation system based on Bluetooth,” in Proceedings of the 21st International Conference on Electronics Communications and Computers (CONIELECOMP '11), pp. 271–277, March 2011.
[6]
S. Chumkamon, P. Tuvaphanthaphiphat, and P. Keeratiwintakorn, “A blind navigation system using RFID for indoor environments,” in Proceedings of the 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON '08), pp. 765–768, tha, May 2008.
[7]
Y. Jiang, Y. Fang, C. Yao, and Z. Wang, “A design of indoor & outdoor navigation system,” in Proceedings of the IET International Conference on Communication Technology and Application (ICCTA '11), pp. 877–881, 2011.
[8]
S. Sch?n and O. Bielenberg, “On the capability of high sensitivity GPS for precise indoor positioning,” in Proceedings of the 5th Workshop on Positioning, Navigation and Communication (WPNC '08), pp. 121–127, Hannover, Germany, March 2008.
[9]
A. Vervisch-Picois and N. Samama, “Interference mitigation in a repeater and pseudolite indoor positioning system,” IEEE Journal of Selected Topics in Signal Processing, vol. 3, no. 5, pp. 810–820, 1932.
[10]
B. Dawes and K.-W. Chin, “A comparison of deterministic and probabilistic methods for indoor localization,” Journal of Systems and Software, vol. 84, no. 3, pp. 442–451, 2011.
[11]
P. Brida, F. Gaborik, J. Duha, and J. Machaj, “Indoor positioning system designed for user adaptive systems,” in Proceedings of the 3rd Asian Conference on Intelligent Information and Database Systems (ACIIDS '11), pp. 237–245, Daegu, South Korea.
[12]
H. Laitinen, J. L?hteenm?ki, and T. Nordstr?m, “Database correlation method for GSM location,” in Proceedings of the IEEE VTS 53rd Vehicular Technology Conference (VTS SPRING '01), pp. 2504–2508, May 2001.
[13]
L. Tsung-Nan and L. Po-Chiang, “Performance comparison of indoor positioning techniques based on location fingerprinting in wireless networks,” in Proceedings of the International Conference on Wireless Networks, Communications and Mobile Computing, vol. 2, pp. 1569–1574, June 2005.
[14]
V. Otsason, Accurate indoor localization using wide GSM fingerprinting [M.S. thesis], Tartu, Estonia, 2005.
[15]
T. Chrysikos, G. Georgopoulos, K. Birkos, and S. Kotsopoulos, “Wireless channel characterization: on the validation issues of indoor RF models at 2.4 GHz,” in Proceedings of the 1st Panhellenic Conference on Electronics and Telecommunications (PACET '09), Patras, Greece, March 2009.
[16]
K. R. Anne, K. Kyamakya, F. Erbas, C. Takenga, and J. C. Chedjou, “GSM RSSI-based positioning using extended Kalman filter for training artificial neural networks,” in Proceedings of the IEEE 60th Vehicular Technology Conference: Wireless Technologies for Global Security (VTC-Fall '04), pp. 4141–4145, Los Angeles, Calif, USA, September 2004.
[17]
V. Honkavirta, T. Per?l?, S. Ali-L?ytty, and R. Piché, “A comparative survey of WLAN location fingerprinting methods,” in Proceedings of the 6th Workshop on Positioning, Navigation and Communication (WPNC '09), pp. 243–251, March 2009.
Ericsson, Ericsson Labs, Ericsson Labs—Indoor Maps, 2011, http://indoor.labs.ericsson.net/.
[20]
P. Brida, J. Benikovsky, and J. Machaj, “Performance investigation of WifiLOC positioning system,” in Proceedings of the 34th International Conference on Telecommunications and Signal Processing (TSP '11), pp. 203–207, Budapest, Hungary, 2011.