ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 425-429, 2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
14 Sep 2017
C. Yu and N. El-Sheimy Geomatics Engineering, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
Keywords: Indoor Location-Based Service (LBS), Wi-Fi-based positioning, Inertial Navigation System (INS), map-aiding indoor position, low-cost Microelectromechanical systems (MEMS) Sensors devices, integrated indoor position method Abstract. In this research, an indoor map aided INS/Wi-Fi integrated location based services (LBS) applications is proposed and implemented on smartphone platforms. Indoor map information together with measurements from an inertial measurement unit (IMU) and Received Signal Strength Indicator (RSSI) value from Wi-Fi are collected to obtain an accurate, continuous, and low-cost position solution. The main challenge of this research is to make effective use of various measurements that complement each other without increasing the computational burden of the system. The integrated system in this paper includes three modules: INS, Wi-Fi (if signal available) and indoor maps. A cascade structure Particle/Kalman filter framework is applied to combine the different modules. Firstly, INS position and Wi-Fi fingerprint position integrated through Kalman filter for estimating positioning information. Then, indoor map information is applied to correct the error of INS/Wi-Fi estimated position through particle filter. Indoor tests show that the proposed method can effectively reduce the accumulation positioning errors of stand-alone INS systems, and provide stable, continuous and reliable indoor location service.
Conference paper (PDF, 2763 KB)

Citation: Yu, C. and El-Sheimy, N.: INDOOR MAP AIDED INS/WI-FI INTEGRATED LBS ON SMARTPHONE PLATFORMS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W4, 425-429,, 2017.

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