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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-3ccb96de-e8d4-4605-957f-d789f1e90c72

Czasopismo

Archiwum Fotogrametrii, Kartografii i Teledetekcji

Tytuł artykułu

Assisting personal positioning in indoor environments using map matching

Autorzy Attia, M.  Moussa, A.  Zhao, X.  El-Sheimy, N. 
Treść / Zawartość
Attia.pdf
Warianty tytułu
Języki publikacji EN
Abstrakty
EN Personal positioning is facing a huge challenge to maintain a reliable accuracy through all applications. Although in outdoor applications, several mobile navigation devices can provide acceptable positioning accuracy, the situation in indoor environment is not the same. Mobile navigation devices mainly contain a global positioning system (GPS) receiver and an inertial measurement unit (IMU). The main drawback in indoor navigation applications is the unavailability of the GNSS signals, which decreases the possibility of obtaining an accurate absolute position solution, as the inertial system (INS) solution will drift with time in the absence of external updates. Several alternatives were presented lately to update the inertial solution such as using Wi-Fi, UWB, RFID, several self-contained sensors, imaging aiding and spatial information aiding. In order to achieve accurate position solution, with low-cost and usable technique, an integrated mobile navigation system integrating GPS/IMU/Wi-Fi and map-matching was developed. The developed system uses the prior knowledge of the indoor geometrical and topological information, as a threshold for the navigation solution, forcing the provided solution to be mostly on the right track. The geometrical and topological information for the building was used to build the geospatial data model. The use of this model was performed by developing a map matching algorithm which uses the geometrical and topological characteristics of the building to locate the user position on the building map. This algorithm was developed based on the geospatial information of the Engineering building, University of Calgary, where the field test occurred. The map-matching algorithm was evaluated by processing and comparing two separate navigation solutions through the study area, one using only the GPS/IMU/Wi-Fi system, and second solution was assisted with the map-matching algorithm which shows significant enhancement in the position solution for the indoor trajectory.
Słowa kluczowe
PL multisensor   GPS/INS   GIS   czas rzeczywisty   matching   nawigacja  
EN multisensor   GPS/INS   GIS   real time   matching   navigation  
Wydawca Zarząd Główny Stowarzyszenia Geodetów Polskich
Czasopismo Archiwum Fotogrametrii, Kartografii i Teledetekcji
Rocznik 2011
Tom Vol. 22
Strony 39--49
Opis fizyczny Bibliogr. 15 poz.
Twórcy
autor Attia, M.
  • Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4, maaattia@ucalgary.ca
autor Moussa, A.
  • Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4, amelsaye@ucalgary.ca
autor Zhao, X.
  • Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4, xinzhao@ucalgary.ca
autor El-Sheimy, N.
  • Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4, elsheimy@ucalgary.ca
Bibliografia
1. Arto, P., Ari-Heikki, S., Merja, H., Jussi, H. and Jonna, H., 2009. Towards designing better maps for indoor navigation: experiences from a case study. the 8th International Conference on Mobile and Ubiquitous Multimedia, Cambridge, United Kingdom: ACM.
2. Attia, M., Moussa, A. and El-Sheimy, N., 2010. Bridging Integrated GPS/INS Systems with Geospatial Models for Car Navigation Applications. ION GNSS conference, Portland, USA.
3. Basnayake, C., Mezentsev, O., Lachapelle, G. and Cannon, M.E., 2005. An HSGPS, inertial and map-matching integrated portable vehicular navigation system for uninterrupted real-time vehicular navigation. Int. J. Vehicle Information and Communication Systems, Vol. 1, Nos. 1/2, pp.131–151.
4. Bullock, J. and Krakiwsky, E., 1994. Analysis of the use of digital road maps in vehicle navigation. IEEE Symposium on Position Location and Navigation, Las Vegas, NV, pp. 494–501.
5. El-Sheimy, N., 2010. Inertial Techniques and INS/DGPS Integration. Lecture Notes, Geomatics Department, University of Calgary.
6. Gillieron, P. and Merminod, B., 2003. Personal navigation system for indoor applications. 11th IAIN World Congress, Berlin, Germany.
7. Glanzer, G., Bernoulli, T., Wiessflecker, T. and Walder, U., 2009. Semi-autonomous indoor positioning using MEMS-based inertial measurement units and building information. 6th Workshop in Positioning, Navigation and Communication WPNC, pp. 135-139.
8. Greenfeld, J., 2002. Matching GPS observations to locations on a digital map. the 81st Annual Meeting of the Transportation Research Board, Washington D.C. .
9. Khider, M., Kaiser, S., Robertson, P. and Angermann, M., 2008. The Effect of Maps-Enhanced Novel Movement Models on Pedestrian Navigation Performance. 12th European Navigation Conference (ENC GNSS).
10. Miesenberger, K., Klaus, J., Zagler, W., Karshmer, A., Shayeganfar, F., Anjomshoaa, A. and Tjoa, A., 2008. A Smart Indoor Navigation Solution Based on Building Information Model and Google Android. Computers Helping People with Special Needs. vol. 5105: Springer Berlin / Heidelberg, pp. 1050-1056.
11. Quddus, M., Ochieng, W. and Noland, R., 2007.Current Map Matching Algorithms for Transport Applications: State-of-the art and Future Research Directions. Transportation research. Part C, Emerging technologies.
12. Quddus, M., Ochieng, W., Zhao, L. and Noland, R., 2003. A general map matching algorithm for transport telematics applications. GPS solutions, Volume 7, Number 3, pp. 157-167.
13. Syed, Z., 2009. Design and Implementation Issues of a Portable Navigation System. PhD thesis, Department of Geomatics engineering, University of Calgary.
14. White, C., Bernstein, D. and Kornhauser, A., 2000. Some map matching algorithms for personal navigation assistants. Transportation Research Part C 8, pp. 91-108.
15. Zhao, X., Goodall, C., Syed, Z., Wright, B. and El-Sheimy, N., 2010. Wi-Fi Assisted Multisensor Personal Navigation System for Indoor Environments. ION ITM conference. USA.
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