基于卡尔曼滤波与中位加权的定位算法

计算机应用 ›› 2014, Vol. 34 ›› Issue (12): 3387-3390.

基于卡尔曼滤波与中位加权的定位算法

肖如良,李奕诺,江少华,梅忠,蔡声镇

福建师范大学软件学院,福州 350117

收稿日期:2014-05-28 修回日期:2014-07-18 出版日期:2014-12-01 发布日期:2014-12-31
通讯作者: 肖如良
作者简介:肖如良(1966-),男,湖南娄底人,教授,博士,CCF高级会员,主要研究方向:算法设计与分析、软件工程; 李奕诺(1989-),男,河南驻马店人,硕士研究生,主要研究方向:机器学习; 江少华(1991-),男,福建泉州人,硕士研究生,主要研究方向:算法设计与分析；梅忠(1988-),男,湖北武汉人,硕士研究生,主要研究方向:机器学习；蔡声镇(1954-),男,福建泉州人,教授,主要研究方向:嵌入式系统。
基金资助:
教育部规划基金资助项目;福建省科技计划重大项目

Indoor positioning based on Kalman filter and weighted median

XIAO Ruliang,LI Yinuo,JIANG Shaohua,MEi Zhong,CAI Shengzhen

Faculty of Software, Fujian Normal University, Fuzhou Fujian 350117, China

Received:2014-05-28 Revised:2014-07-18 Online:2014-12-01 Published:2014-12-31
Contact: XIAO Ruliang
Supported by:
Science and Technology Program Key Project of Fujian Province of China

摘要/Abstract

摘要：

为了有效解决基于接收信号强度的高精度室内位置服务计算困难问题,提出了一种新的基于卡尔曼滤波和中位加权(WMKF)的定位算法。该算法不同于以往的室内定位算法,首先应用卡尔曼滤波平滑了随机误差；然后利用中位加权方法抑制了显著误差,利用距离路径损耗模型得到衰落曲线并计算出估计距离；最后利用质心求解方法得到目标节点位置。实验结果表明,该算法初步解决了相对复杂环境下定位稳定性较差的问题,并有效地提高了定位精度,使精度达到0.81~1m。

Abstract:

In order to solve the problem of high-precise indoor positioning calculation using received signal strength, a novel WMKF (Kalman Filtering and Weighted Median) positioning algorithm was proposed. The algorithm was different from previous indoor localization algorithms. Firstly, Kalman filter method was used to smooth random error, and weighted median method was made to reduce the influence of gross error, then the log distance path loss model was used to obtain the decline curve and calculate the estimated distance. Finally, the centroid method was used to get the position of the target node. The experimental results show that, this WMKF algorithm initially improve that the poor stability of positioning in a relatively complex environment, and effectively enhanced the positioning accuracy, making the accuracy between 0.81m to 1m.

中图分类号:

TP319

肖如良李奕诺江少华梅忠蔡声镇. 基于卡尔曼滤波与中位加权的定位算法[J]. 计算机应用, 2014, 34(12): 3387-3390.

XIAO Ruliang LI Yinuo JIANG Shaohua MEi Zhong CAI Shengzhen. Indoor positioning based on Kalman filter and weighted median[J]. Journal of Computer Applications, 2014, 34(12): 3387-3390.

参考文献

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