CLC number: TN92
On-line Access: 2021-07-12
Received: 2020-03-03
Revision Accepted: 2020-10-25
Crosschecked: 2020-12-24
Cited: 0
Clicked: 4413
Citations: Bibtex RefMan EndNote GB/T7714
Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao. Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge regression[J]. Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/FITEE.2000093 @article{title="Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge regression", %0 Journal Article TY - JOUR
基于改进型分簇和核岭回归的RSS室内定位算法上海理工大学光电信息与计算机工程学院,中国上海市,200093 摘要:智能移动设备和无线传感器网络相关技术的融合发展,使得基于位置的服务受到广泛关注。如何利用无线信号在室内复杂环境下实时获得理想的定位精度,成为当前研究热点之一。提出一种基于接收信号强度(RSS, received signal strength)的位置指纹定位算法。该算法分为离线和在线阶段。离线阶段采用一种改进的分簇方法,采用K中心点分簇算法,把物理位置位于簇外边缘的参考点加入簇指纹库,使得参考位置点的RSS信号特性与物理位置结合。在线定位时,基于簇匹配的粗定位与簇内二次精确定位结合。簇内定位采用基于核岭回归的算法,通过核函数实现RSS信号特性与物理位置非线性关系挖掘,同时算法在簇内成员中进行,减小了时间复杂度。通过两个典型室内环境下的定位实验,探究了基于RSS信号强度和覆盖向量的两种分簇和簇匹配准则对算法性能的影响,以及不同环境下参数的选择,验证了所提算法的定位性能。 关键词组: Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article
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