物联网中基于扩展卡尔曼滤波的移动群体定位
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  • 英文篇名:Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things
  • 作者:梁玉珠 ; 沈雪微 ; 邱磊 ; 陈柏生 ; 王田
  • 英文作者:LIANG Yu-zhu;SHEN Xue-wei;QIU Lei;CHEN Bai-sheng;WANG Tian;College of Computer Science and Technology,Huaqiao University;The State Key Laboratory of Internet of Things for Smart City,University of Macau;
  • 关键词:协作式定位 ; 卡尔曼滤波 ; 定位效率 ; 移动群体
  • 英文关键词:cooperative localization;;Kalman filter;;localization performance;;mobile groups
  • 中文刊名:BJYD
  • 英文刊名:Journal of Beijing University of Posts and Telecommunications
  • 机构:华侨大学计算机科学与技术学院;澳门大学智能城市物联网国家重点实验室;
  • 出版日期:2019-05-08 10:31
  • 出版单位:北京邮电大学学报
  • 年:2019
  • 期:v.42
  • 基金:福建省社会科学规划基金项目(FJ2018B038);; 福建省自然科学基金项目(2018J01092);; 福建省教育厅中青年教师教育科研基金项目(JAT170040);; 华侨大学研究生科研创新基金项目(17013083005)
  • 语种:中文;
  • 页:BJYD201902016
  • 页数:6
  • CN:02
  • ISSN:11-3570/TN
  • 分类号:99-104
摘要
为了满足高精度和高可靠性定位的需求,提出了一种基于扩展卡尔曼滤波的移动群体定位算法,把待定位的用户节点当成一个群组,利用他们之间的距离信息得到更好的定位性能,以减小环境噪声和无线信号不稳定造成的影响.此外,开发出一个实际的系统,并在大学校园里进行了大量实验.实验结果和理论分析验证了所提出方法的有效性.
        In order to meet the requirement of high localization accuracy and the high reliable localization in some scenarios,the user nodes to be located were taken as a group to get better localization performance by utilizing the mutual distance information among them. A mobile group localization method was designed based on extended Kalman filter,which can alleviate the influence caused by environmental noisy and unstable wireless signals. Besides,a real system was implemented and experiments were performed on the campus of University. The experimental evaluations prove that the performance of the proposed method can effectively improve the localization accuracy.
引文
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