Ouyang Guanglie, Abed-Meraim Karim
Laboratoire Pluridisciplinaire de Recherche en Ingénierie des Systèmes, Mécanique et Energétique, Université d'Orléans, 12 Rue de Blois, 45067 Orleans, France.
Sensors (Basel). 2022 May 25;22(11):4014. doi: 10.3390/s22114014.
Infrastructure-free magnetic fields are ubiquitous and have attracted tremendous interest in magnetic field-based indoor positioning. However, magnetic field-based indoor positioning applications face challenges such as low discernibility, heterogeneous devices, and interference from ferromagnetic materials. This paper first analyzes the statistical characteristics of magnetic field (MF) measurements from heterogeneous smartphones. It demonstrates that, in the absence of disturbances, the MF measurements in indoor environments follow a Gaussian distribution with temporal stability and spatial discernibility. It shows the fluctuations in magnetic field intensity caused by the rotation of a smartphone around the Z-axis. Secondly, it suggests that the RLOWESS method can be used to eliminate magnetic field anomalies, using magnetometer calibration to ensure consistent MF measurements in heterogeneous smartphones. Thirdly, it tests the magnetic field positioning performance of homogeneous and heterogeneous devices using different machine learning methods. Finally, it summarizes the feasibility/limitations of using only MF measurement for indoor positioning.
无基础设施的磁场无处不在，在基于磁场的室内定位方面引起了极大关注。然而，基于磁场的室内定位应用面临着诸如辨别力低、设备异构以及来自铁磁材料的干扰等挑战。本文首先分析了来自异构智能手机的磁场（MF）测量的统计特性。结果表明，在无干扰情况下，室内环境中的MF测量遵循具有时间稳定性和空间辨别力的高斯分布。它展示了智能手机绕Z轴旋转引起的磁场强度波动。其次，建议使用RLOWESS方法消除磁场异常，利用磁力计校准确保异构智能手机中MF测量的一致性。第三，使用不同的机器学习方法测试了同类和异构设备的磁场定位性能。最后，总结了仅使用MF测量进行室内定位的可行性/局限性。
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