首页> 外文期刊>IEEE transactions on mobile computing >Kernel-Based Positioning in Wireless Local Area Networks
【24h】

Kernel-Based Positioning in Wireless Local Area Networks

机译:无线局域网中基于内核的定位

获取原文
获取原文并翻译 | 示例

摘要

The recent proliferation of location-based services (LBSs) has necessitated the development of effective indoor positioning solutions. In such a context, wireless local area network (WLAN) positioning is a particularly viable solution in terms of hardware and installation costs due to the ubiquity of WLAN infrastructures. This paper examines three aspects of the problem of indoor WLAN positioning using received signal strength (RSS). First, we show that, due to the variability of RSS features over space, a spatially localized positioning method leads to improved positioning results. Second, we explore the problem of access point (AP) selection for positioning and demonstrate the need for further research in this area. Third, we present a kernelized distance calculation algorithm for comparing RSS observations to RSS training records. Experimental results indicate that the proposed system leads to a 17 percent (0.56 m) improvement over the widely used K-nearest neighbor and histogram-based methods
机译:最近,基于位置的服务(LBS)激增,因此必须开发有效的室内定位解决方案。在这种情况下,由于WLAN基础设施的普遍存在,就硬件和安装成本而言,无线局域网(WLAN)定位是一种特别可行的解决方案。本文使用接收信号强度(RSS)研究了室内WLAN定位问题的三个方面。首先,我们表明,由于RSS功能在空间上的可变性,空间局部定位方法可改善定位结果。其次,我们探讨了用于定位的接入点(AP)选择的问题,并说明了在该领域需要进一步研究的必要性。第三,我们提出了一种内核化的距离计算算法,用于将RSS观察结果与RSS训练记录进行比较。实验结果表明,与广泛使用的K最近邻和基于直方图的方法相比,该系统可将结果提高17%(0.56 m)

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号