Adaptive motion model for a smart phone based opportunistic localization system
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Indoor pedestrian displacement estimation using Smart phone inertial sensors
International Journal of Innovative Computing and Applications
Virtual lifeline: Multimodal sensor data fusion for robust navigation in unknown environments
Pervasive and Mobile Computing
Proceeding of the 11th annual international conference on Mobile systems, applications, and services
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The accelerometers integrated in today’s phones can be used to estimate the distance travelled from the accelerations made while walking. The placement of the sensor on the body is important to take into consideration. In this paper, the accelerations recorded with a daily-used phone in the trouser pocket were processed on a mobile device to detect steps and estimate the distance travelled. The outcome of the distance estimates shows an error of 0.05 metres per one metre and can be improved through calibration. This distance was applied in the motion model of a particle filter, and fused with a map of the building. The results establish that the estimates of the algorithm are valuable when fusing with other technologies or environment information, to aid the estimation of the location.