A Magnetic-Based Indoor Positioning Method on Fingerprint and Confidence Evaluation

A high accuracy in positioning and navigation is difficult in indoor and underground conditions due to obstacles. To deal with the issues of inaccurate positioning in indoor and underground environments, a novel Magnetic Based Positioning System (MBPS) based on fingerprint and confidence evaluation is presented in this article. The proposed method promises good penetrability and negligible interference from multipath error, along with solving the sparse fingerprint problem constrained by the a priori condition. Furthermore, to address the problem of variable signal quality, an optimal information selection method based on confidence evaluation is proposed. This method suggests evaluating and selecting the optimal information source to improve the robustness and accuracy of the MBPS. The approach is supported by experiments, where magnetic beacons are detected behind a concrete wall of 0.3 m thickness. According to the experimental results, the positioning accuracy can reach up to 0.040 m. This work provides an impressive positioning solution for indoor, underground, and other scenarios where high-frequency wireless signals cannot be used due to the obstacles.