Indoor Geomagnetic Positioning Based on Joint Algorithm of Particle Filter

The indoor geomagnetic field is affected by the presence of a steel structure and other ferromagnetic materials, causing local anomalies in the magnetic field region and and a unique indoor magnetic field. Indoor geomagnetic positioning technology can be realized by exploiting this phenomenon. However, in large buildings, the specificity of the geomagnetic field is weakened, which leads to the distortion of positioning results. To overcome this problem, an indoor geomagnetic positioning technology based on path matching was proposed, which increases the number of matching features. A new joint algorithm was used combining the dynamic time warp algorithm with the particle filter algorithm, which can track the target in a path matching mode. In the matching process, the similarity between the paths was determined by calculating the Spearman correlation coefficient, to assist the positioning. Finally, experimental verification was performed using a measuring robot loaded with a magnetic sensor. The results show that the path matching exhibits a sufficient number of geomagnetic features, which can overcome the phenomenon of blurring the positioning results under the condition of weakening specificity, and the positioning accuracy is higher than 1 m.