论文标题

OUTFIN,一种基于指纹方法的多设备和多模式数据集,用于户外本地化

OutFin, a multi-device and multi-modal dataset for outdoor localization based on the fingerprinting approach

论文作者

Alhomayani, Fahad, Mahoor, Mohammad H.

论文摘要

近年来,基于指纹的定位引起了研究人员的关注,因为它是全球导航卫星系统和基于蜂窝网络的本地化的有希望的替代品。尽管如此,研究人员可能会用来开发,评估和比较基于指纹的定位解决方案的公共可用数据集构成研究的高障碍。为了克服这一障碍和促进新的研究工作,本文介绍了Outfin,这是一个新颖的户外位置指纹数据集,使用两种不同的智能手机收集。 OUTFIN包括不同的数据类型,例如WiFi,蓝牙和细胞信号强度,除了来自各种传感器的测量值,包括磁力计,加速度计,陀螺仪,气压计和环境光传感器。收集区跨越了四个分散的站点,共有122个参考点。每个站点在全球导航卫星系统以及参考点号,安排和间距方面的可见性都不同。在向公众开放之前,进行了几项实验以验证其技术质量。

In recent years, fingerprint-based positioning has gained researchers attention since it is a promising alternative to the Global Navigation Satellite System and cellular network-based localization in urban areas. Despite this, the lack of publicly available datasets that researchers can use to develop, evaluate, and compare fingerprint-based positioning solutions constitutes a high entry barrier for studies. As an effort to overcome this barrier and foster new research efforts, this paper presents OutFin, a novel dataset of outdoor location fingerprints that were collected using two different smartphones. OutFin is comprised of diverse data types such as WiFi, Bluetooth, and cellular signal strengths, in addition to measurements from various sensors including the magnetometer, accelerometer, gyroscope, barometer, and ambient light sensor. The collection area spanned four dispersed sites with a total of 122 reference points. Each site is different in terms of its visibility to the Global Navigation Satellite System and reference points number, arrangement, and spacing. Before OutFin was made available to the public, several experiments were conducted to validate its technical quality.

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