Accurate Indoor 3D Location Based on MEMS/Vision by Using A Smartphone

Indoor localization using embedded multi-sensors has attracted considerable attention over the past decades. However, traditional localization solutions usually either depend heavily on elaborate scenes with infrastructure layout or provide inertial-based results with severely degraded accuracy in a long-term positioning environment. Multi-story complex buildings require accurate indoor positioning results, including height information, while previous studies rarely involved indoor 3D location research. This paper proposes an accurate indoor 3D location algorithm based on MEMS/vision by using a smartphone. We make full use of both visual and inertial modal information. Visual positioning is used to achieve global positioning, while relative positioning is based on traditional PDR. First, the MEMS-based relative positioning solution is proposed to determine 3D position by using complementary filter. Secondly, efficient image-based localization (IBL) algorithm is employed, and we use the prior attitude information to obtain the geometric constraint for the global map and improve efficiency of 2D-3D correspondence. Moreover, we apply a dynamic fusion strategy to integrate the MEMS-based results and visual-based locations, providing the accurate 3D position continuously by using relative and global solutions. Experiments conducted in typical indoor scenes showed that the proposed localization system can obtain decimeter 3D position most time (over 85% 3D location errors are within 0.45 m), which effectively mitigates the cumulative errors of low-cost IMU.