[1]王 群,李宗骍,李千目,等.基于实时运动状态的RSSI测距室内定位算法[J].南京理工大学学报(自然科学版),2015,39(02):229-235.
 Wang Qun,Li Zongxing,Li Qianmu,et al.Indoor localization algorithm based on real time state of motion and RSSI ranging[J].Journal of Nanjing University of Science and Technology,2015,39(02):229-235.
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基于实时运动状态的RSSI测距室内定位算法
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
39卷
期数:
2015年02期
页码:
229-235
栏目:
出版日期:
2015-04-30

文章信息/Info

Title:
Indoor localization algorithm based on real time state of motion and RSSI ranging
作者:
王 群12李宗骍1李千目1张 宏1
1.南京理工大学 计算机科学与工程学院,江苏 南京 210094; 2.江苏警官学院 计算机信息与网络安全系,江苏 南京 210031
Author(s):
Wang Qun12Li Zongxing1Li Qianmu1Zhang Hong1
1.School of Computer Science and Engineering,NUST,Nanjing 210094,China; 2.Department of Computer Information and Cyber Security,Jiangsu Police Institute,Nanjing 210031,China
关键词:
室内定位 接收信号强度指示器测距 实时运动状态测距 线性回归估计 中值滤波
Keywords:
indoor locatization received signal strength indication ranging real-time motion states ranging linear regression estimate median filter
分类号:
TP309
摘要:
为了减少室内定位的硬件成本,提高定位效率,该文提出一种与低成本的接收信号强度指示器(RSSI)距离测量技术相融合、利用人体室内低速运动特性进行位置状态预测的室内定位算法。分析了一种RSSI测距模型及基于运动状态的测距预测模型,并设计测距实验获取实际运动验证数据。在算法和模型中,使用中值滤波和均值处理方式,对所获取实验数据和参数进行采样和滤波处理,降低了环境变化对数据的影响,提高了数据可信度。通过对实验数据进行线性回归分析,合理选取定位模型中各项参数值,最终用实际测距结果分析了验证所提出的算法。实验证明,该
Abstract:
For reducing the cost of hardware deployment and improving the efficiency of the indoor localization,an indoor localization algorithm combining an indoor location state prediction of low-speed movement characteristics of human with a low-cost indoor algorithm based on the received signal strength indication(RSSI)ranging technology is presented.By analyzing a distance measurement model and a predictive model based on the state of motion,a ranging experiment model is designed to gain multiple sets of data for validation.The algorithms and models take samples and deal with experimental data and the parameters by the median filter and average value processing,reducing the influence of environmental change on the data and improving data reliability.Every parameter is rationally selected from model parameters through the linear regression analysis of experimental data.The experiment analyzes and validates the proposed analysis algorithm through the actual final results.The experiment indicates that the method can improve ranging anti-jamming capability of RSSI and reduce the cost of hardware deployment.The ranging error is about 1.3 m when the longest distance of a node is about 5 m and the other nodes are evenly distributed.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-04-21 修回日期:2014-11-23
基金项目:国家自然科学基金(61272419); 江苏省高等学校重点学科建设专项资助(JS110838); 江苏省未来网络前瞻性研究项目(BY2013095-02); 江苏省产学研前瞻性项目(BY2014089); 连云港国际合作项目(CH1304)
作者简介:王群(1971-),男,教授,主要研究方向:传感网与信息安全,E-mail:wangqun@jspi.edu.cn; 通讯作者:李千目(1979-),男,博士,教授,博士生导师,主要研究方向:无线传感网、网络安全、物联网,E-mail:274365054@qq.com。
引文格式:王群,李宗骍,李千目,等.基于实时运动状态的RSSI测距室内定位算法[J].南京理工大学学报,2015,39(2):229-235.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2015-04-30