Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments.
Adaptive Indoor Positioning Model Based on WLAN-Fingerprinting for Dynamic and Multi-Floor Environments.
复制标题
DOI：
10.3390/s17081789
复制
发表时间：
2017-08-05
期刊：
影响因子：
--
通讯作者：
Firdaus F
中科院分区：
文献类型：
--
作者：
Alshami IH;Ahmad NA;Sahibuddin S;Firdaus F
全球定位系统展示了基于位置的服务的重要性，但由于卫星和接收器之间缺乏视线，它不能在室内使用。需要室内定位系统来提供室内基于位置的服务。无线局域网指纹是室内定位系统的最佳选择之一，因为它们的成本低，精度高，但它们有许多缺点：创建无线电地图是耗时的，无线电地图将随着任何环境的变化而变得过时，不同的移动的设备读取接收信号强度（RSS）不同，以及人们在接入点和移动的设备之间的LOS中的存在影响RSS。本研究提出了一种新的自适应室内定位系统模型（称为DIPS），其基于：动态无线电地图生成器、RSS确定性技术以及动态和多楼层环境的人员在场效应集成。动态在我们的上下文中是指人和设备异质性的影响。DIPS对楼层和房间的定位精度分别达到98%和92%，单点定位误差达到1.2m。RSS确定性将不同移动的设备的地板和房间的定位准确度提高了11%和9%。考虑人的在场效应后，误差减小了0.2m。与其他作品相比，DIPS实现了更好的定位没有额外的设备。
The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS) differently, and peoples’ presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS) based on: a dynamic radio map generator, RSS certainty technique and peoples’ presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples’ presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.
登录
查看更多内容
影响因子：
7.9
作者：
Atia, Mohamed M.;Noureldin, Aboelmagd;Korenberg, Michael J.
通讯作者：
Korenberg, Michael J.
影响因子：
4.3
作者：
Chen, Lyu-Han;Wu, Eric Hsiao-Kuang;Chen, Gen-Huey
通讯作者：
Chen, Gen-Huey
影响因子：
7.9
作者：
Figuera, Carlos;Luis Rojo-Alvarez, Jose;Ramos-Lopez, Javier
通讯作者：
Ramos-Lopez, Javier
影响因子：
2.2
作者：
Gezici, Sinan
通讯作者：
Gezici, Sinan
DOI：
10.3390/s17061213
发表时间：
2017-05-25
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Ali MU;Hur S;Park Y
通讯作者：
Park Y