Hybrid technique for indoor positioning system based on Wi-Fi received signal strength indication
Hybrid technique for indoor positioning system based on Wi-Fi received signal strength indication
复制标题
基于Wi-Fi接收信号强度指示的室内定位系统混合技术
DOI：
10.1109/ipin.2014.7275467
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Dongkai Yang
中科院分区：
文献类型：
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作者：
Peerapong Torteeka;C. Xiu;Dongkai Yang
近年来，基于无线接入设备接收信号强度指示(RSSI)的室内定位系统变得非常流行。该系统在许多应用中非常有用，例如为生活社区内的老年人或客户提供跟踪服务、移动机器人定位、物流系统等。而使用全球导航卫星系统（GNSS）和蜂窝网络的室外环境运行良好并广泛用于导航。然而，卫星或蜂窝基站的信号传播存在问题。它们无法在复杂的建筑区域甚至城市环境中有效使用。总的来说，广泛使用的基于Wi-Fi的室内环境定位方法主要有两类，即三边测量技术和位置指纹技术（LF）。众所周知，三边测量技术的显式定位性能比低频技术对噪声影响更敏感。然而，LF技术的准确性取决于训练数据集，当环境发生变化时，它就不能很好地发挥作用。在本文中，我们提出了混合算法，结合了两个系统的优点，能够提高精度稳定性和鲁棒性。通过实验结果对该算法的性能进行了评估，表明我们提出的方案能够达到一定水平的定位系统精度。
An indoor positioning system based on Receive Signal Strength Indication(RSSI) from wireless access equipment has become very popular in recent years. This system is very useful in many applications such as tracking service for older people or customer inside living communities, mobile robot localization, logistics systems etc. While outdoor environment using Global Navigation Satellite System(GNSS) and cellular network work well and are widespread used for navigation. However, there is a problem with signal propagation from satellites or cell site. They cannot be used effectively inside complex building areas or even in an urban environment. In general, the widely used method for indoor environment positioning based on Wi-Fi consists with two main categories, which are trilateration technique and location fingerprint technique(LF). It is already known that the explicit positioning performance of trilateration technique is more sensitive to noise effect than LF technique. Nevertheless, the accuracy of LF technique depends on training data set and it does not work well when environment changes. In this article, we propose the hybrid algorithm, the combination of the advantages of both systems, which is able to improve the accuracy stability and robustness. The performance of this algorithm is evaluated by the experimental results, which shows that our proposed scheme can achieve a certain level of positioning system accuracy.