Abstract
With the continual advancement of positioning technology, people's use of mobile devices has increased substantially. The global navigation satellite system (GNSS) has improved outdoor positioning performance. However, it cannot effectively locate indoor users owing to signal masking effects. Common indoor positioning technologies include radio frequencies, image visions, and pedestrian dead reckoning. However, the advantages and disadvantages of each technology prevent a single indoor positioning technology from solving problems related to various environmental factors. In this study, a hybrid method was proposed to improve the accuracy of indoor positioning by combining visual simultaneous localization and mapping (VSLAM) with a magnetic fingerprint map. A smartphone was used as an experimental device, and a built-in camera and magnetic sensor were used to collect data on the characteristics of the indoor environment and to determine the effect of the magnetic field on the building structure. First, through the use of a preestablished indoor magnetic fingerprint map, the initial position was obtained using the weighted k-nearest neighbor matching method. Subsequently, combined with the VSLAM, the Oriented FAST and Rotated BRIEF (ORB) feature was used to calculate the indoor coordinates of a user. Finally, the optimal user's position was determined by employing loose coupling and coordinate constraints from a magnetic fingerprint map. The findings indicated that the indoor positioning accuracy could reach 0.5 to 0.7 m and that different brands and models of mobile devices could achieve the same accuracy.