The use of wireless signals for purposes of localization enables a host of applications relating to the determination and verification of the positions of network participants, ranging from radar to satellite navigation. Consequently, it has been a longstanding interest of theoretical and practical research in mobile networks and many solutions have been proposed in the scientific literature. However, it is hard to assess the performance of these in the real world and, more severely, to compare their advantages and disadvantages in a controlled scientific manner. With this work, we attempt to improve the current state of the art in localization research and put it on a solid scientific grounding for the future. Concretely, we develop LocaRDS, an open reference dataset of real-world crowdsourced flight data featuring more than 222 million measurements from over 50 million transmissions recorded by 323 sensors. We show how LocaRDS can be used to test, analyze and directly compare different localization techniques and further demonstrate its effectiveness by examining the open question of the aircraft localization problem in crowdsourced sensor networks. Finally, we provide a working reference implementation for the aircraft localization problem and a discussion of possible metrics for use with LocaRDS.
翻译:利用无线信号实现本地化,使得在确定和核实网络参与者从雷达到卫星导航等位置时,能够应用一系列与确定和核实网络参与者位置有关的应用,因此,对移动网络进行理论和实践研究的长期兴趣,科学文献中提出了许多解决办法,然而,很难评估这些网络在现实世界的性能,更严重的是,难以以受控制的科学方式比较其优缺点。通过这项工作,我们试图改进本地化研究的目前水平,将其置于坚实的科学基础。具体地说,我们开发了LocARDS,这是真实世界众源飞行数据的公开参考数据集,从323个传感器记录的5 000多万次传输中测量出2.22亿次以上的数据。我们展示了如何利用LocaRDS测试、分析和直接比较不同的本地化技术,并通过审查众源传感器网络的飞机本地化问题这一公开问题,进一步证明其有效性。我们为飞机本地化问题提供了工作参考实施方法,并讨论了与LocaRDS公司一起使用的可能指标。