Assisting personal positioning in indoor environments using map matching

• Autorzy: Attia M. , Moussa A. , Zhao X. , El-Sheimy N.
• 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

EN

multisensor; GPS/INS; GIS; real time; matching; navigation

PL

multisensor; GPS/INS; GIS; czas rzeczywisty; matching; nawigacja

• 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

autor

Moussa A.

• Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4

autor

Zhao X.

• Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4

autor

El-Sheimy N.

• Mobile Multi-Sensor Systems (MMSS) Research Group, Department of Geomatics Engineering, University of Calgary, Alberta, Canada, T2N1N4

Bibliografia

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• 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.
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• 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. .
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• 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.
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• 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.