Wielandt Stijn, Strycker Lieven De
Dramco Research Group, Faculty of Engineering Technology, Electronics, KU Leuven, Gebroeders De Smetstraat 1, 9000 Ghent, Belgium.
Sensors (Basel). 2017 Nov 2;17(11):2522. doi: 10.3390/s17112522.
Indoor radio frequency positioning systems enable a broad range of location aware applications. However, the localization accuracy is often impaired by Non-Line-Of-Sight (NLOS) connections and indoor multipath effects. An interesting evolution in widely deployed communication systems is the transition to multi-antenna devices with beamforming capabilities. These properties form an opportunity for localization methods based on Angle of Arrival (AoA) estimation. This work investigates how multipath propagation can be exploited to enhance the accuracy of AoA localization systems. The presented multipath assisted method resembles a fingerprinting approach, matching an AoA measurement vector to a set of reference vectors. However, reference data is not generated by labor intensive site surveying. Instead, a ray tracer is used, relying on a-priori known floor plan information. The resulting algorithm requires only one fixed receiving antenna array to determine the position of a mobile transmitter in a room. The approach is experimentally evaluated in LOS and NLOS conditions, providing insights in the accuracy and robustness. The measurements are performed in various indoor environments with different hardware configurations. This leads to the conclusion that the proposed system yields a considerable accuracy improvement over common narrowband AoA positioning methods, as well as a reduction of setup efforts in comparison to conventional fingerprinting systems.
室内射频定位系统支持广泛的位置感知应用。然而，定位精度常常受到非视距（NLOS）连接和室内多径效应的影响。广泛部署的通信系统中一个有趣的发展趋势是向具有波束成形能力的多天线设备过渡。这些特性为基于到达角（AoA）估计的定位方法创造了机会。这项工作研究了如何利用多径传播来提高AoA定位系统的精度。所提出的多径辅助方法类似于一种指纹识别方法，将AoA测量向量与一组参考向量进行匹配。然而，参考数据并非通过劳动强度大的现场勘测生成。相反，使用了一种射线追踪器，它依赖于先验已知的楼层平面图信息。最终的算法只需要一个固定的接收天线阵列就能确定移动发射机在房间中的位置。该方法在视距和非视距条件下进行了实验评估，提供了关于精度和鲁棒性的见解。测量在具有不同硬件配置的各种室内环境中进行。由此得出的结论是，与常见的窄带AoA定位方法相比，所提出的系统在精度上有显著提高，并且与传统的指纹识别系统相比，设置工作量有所减少。
