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Indoor Geomagnetic Positioning Based on a Joint Algorithm of Particle Filter and Dynamic Time Warp

机译:基于粒子滤波和动态时间扭曲联合算法的室内地磁定位

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摘要

The indoor geomagnetic field is affected by the steel structure and other ferromagnetic materials, resulting in the local anomaly of the magnetic field and the indoor geomagnetic field will be specificity. Benefit from this phenomenon, indoor magnetic positioning technology to be achieved. However, in large buildings, the specificity of geomagnetic field will be weakened, which leads to ambiguous positioning results. In response to this phenomenon, this paper presents a path matching based indoor geomagnetic positioning system, by increasing the number of matching features to solve this problem. The system combines Dynamic Time Warp (DTW) algorithm and Particle Filter (PF) algorithm to track the target in the path matching mode. Finally, Measuring robot loaded with magnetic sensor used to verify the results. The results show that the path matching has sufficient number of geomagnetic features to resolve the ambiguity of positioning results under condition of reduced specificity, and the positioning accuracy is better than 1 meter.
机译:室内地磁场受钢结构和其他铁磁材料的影响,导致局部磁场异常,室内地磁场将具有特异性。受益于这种现象,室内磁定位技术得以实现。但是,在大型建筑物中,地磁场的特异性会减弱,从而导致定位结果不明确。针对这种现象,本文提出了一种基于路径匹配的室内地磁定位系统,通过增加匹配特征的数量来解决这个问题。该系统结合了动态时间扭曲(DTW)算法和粒子滤波(PF)算法,以路径匹配模式跟踪目标。最后,装有磁性传感器的测量机器人用于验证结果。结果表明,路径匹配具有足够的地磁特征,可以在降低特异性的情况下解决定位结果的不确定性,定位精度优于1米。

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