School of Automation, Guangdong University of Technology, Guangzhou 510006, China.
French Argentine International Center for Information and Systems Sciences, National Scientific and Technical Research Council, 2000 Rosario, Argentina.
Sensors (Basel). 2020 May 18;20(10):2854. doi: 10.3390/s20102854.
Indoor positioning using Wi-Fi signals is an economic technique. Its drawback is that multipath propagation distorts these signals, leading to an inaccurate localization. An approach to improve the positioning accuracy consists of using fingerprints based on channel state information (CSI). Following this line, we propose a new positioning method which consists of three stages. In the first stage, which is run during initialization, we build a model for the fingerprints of the environment in which we do localization. This model permits obtaining a precise interpolation of fingerprints at positions where a fingerprint measurement is not available. In the second stage, we use this model to obtain a preliminary position estimate based only on the fingerprint measured at the receiver's location. Finally, in the third stage, we combine this preliminary estimation with the dynamical model of the receiver's motion to obtain the final estimation. We compare the localization accuracy of the proposed method with other rival methods in two scenarios, namely, when fingerprints used for localization are similar to those used for initialization, and when they differ due to alterations in the environment. Our experiments show that the proposed method outperforms its rivals in both scenarios.
基于 Wi-Fi 信号的室内定位是一种经济的技术。其缺点是多径传播会使这些信号失真，导致定位不准确。一种提高定位精度的方法是使用基于信道状态信息 (CSI) 的指纹。在此基础上，我们提出了一种新的定位方法，该方法包括三个阶段。在初始化阶段，我们为定位环境的指纹建立一个模型。该模型允许在没有指纹测量的位置进行指纹的精确插值。在第二阶段，我们仅使用在接收器位置测量的指纹，使用该模型获得初步的位置估计。最后，在第三阶段，我们将这个初步估计与接收器运动的动力学模型结合起来，以获得最终的估计。我们在两种情况下将所提出的方法与其他竞争方法的定位精度进行了比较，即当用于定位的指纹与用于初始化的指纹相同时，以及当由于环境变化而不同时。我们的实验表明，在所提出的方法在这两种情况下都优于其他竞争方法。
