基于动态射频指纹的调频定位方法

doi:10.11772/j.issn.1001-9081.2014.11.3173

计算机应用 ›› 2014, Vol. 34 ›› Issue (11): 3173-3176.DOI: 10.11772/j.issn.1001-9081.2014.11.3173

• 2014年全国开放式分布与并行计算学术年会(DPCS 2014)论文 • 上一篇下一篇

基于动态射频指纹的调频定位方法

何艳军¹,²,罗海勇²,戴永¹,陈自力³

1. 湘潭大学信息工程学院,湖南湘潭 411100
2. 中国科学院计算技术研究所,北京 100190;
3. 北京三星通信研究院,北京 100028

收稿日期:2014-07-28 修回日期:2014-08-06 出版日期:2014-11-01 发布日期:2014-12-01
通讯作者: 何艳军
作者简介:何艳军(1988-),男,湖南永州人,硕士研究生,主要研究方向:嵌入式系统;罗海勇(1967-),男,湖北麻城人，高级工程师,〖BP(〗硕士生导师,〖BP)〗博士,主要研究方向:智能定位、物联网、普适计算、嵌入式系统;戴永(1956-),男,湖南湘潭人，〖BP(〗硕士生导师,〖BP)〗教授，主要研究方向:现代模式识别、城市公共安全、嵌入式系统;陈自力(1972-),女,湖北随州人，硕士，〖BP(〗【北京三星通信研究院首席工程师兼项目经理,〖BP)〗主要研究方向:室内定位、移动互联网业务、嵌入式软件。
基金资助:
国家自然科学基金资助项目;国家科技重大专项;国家863计划项目;太原市—中关村合作专项

Frequency modulation location method based on dynamic radio

HE Yanjun¹,²,LUO Haiyong²,Yong DAI³,CHEN Zili⁴

1.
2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China;
3. College of Information Engineering, Xiangtan University, Xiangtan Hunan 411100, China;
4. Beijing Samsung Telecommunications Research Institute, Beijing 100028, China

Received:2014-07-28 Revised:2014-08-06 Online:2014-11-01 Published:2014-12-01
Contact: HE Yanjun

摘要/Abstract

摘要：

针对调频(FM)广播信号动态变化对定位性能产生较大影响的问题,提出了动态射频指纹的FM定位方法。该方法采用多元线性回归和神经网络方法,根据离线阶段各个参考点和部分较准点的调频广播信号强度的关系,使用在线阶段较准点的信号强度实时估计在线阶段参考点的信号强度。通过这两种方法建立具有自适应能力的动态射频地图,并使用贝叶斯估计方法对目标进行定位。实验结果表明,相对静态射频指纹模型：采用多元线性回归的射频指纹动态映射模型定位误差平均减少9.1%,采用神经网络的射频指纹动态映射模型定位误差平均减少36.3%,有效抑制了射频信号动态变化时变性对定位性能的影响。

Abstract:

In view of the fast that dynamic changes of Frequency Modulation (FM) radio signal have great influence on the positioning performance, a localization method based on dynamic radio map was proposed. During offline phase, the relationship between radio signal strength of a few calibration points and each reference point was established by multiple linear regression and neural network, and then during online phase, the real-time radio signal strength values at all reference points were predicted based on the radio signal strength collected at calibration points in real-time. Dynamic map of radio frequency with adaptive ability was established using these two methods, and Bayesian estimation method was used to locate the target. The experimental results show that, compared with static radio map, the multiple linear regression model would reduce the deviation by 9.1%, and the neural network model would reduce the deviation by 36.3%, which restrains the negative impact of radio signal's time-dependent nature to the position performance.

中图分类号:

何艳军罗海勇戴永陈自力. 基于动态射频指纹的调频定位方法[J]. 计算机应用, 2014, 34(11): 3173-3176.

HE Yanjun LUO Haiyong Yong DAI CHEN Zili. Frequency modulation location method based on dynamic radio[J]. Journal of Computer Applications, 2014, 34(11): 3173-3176.

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基于动态射频指纹的调频定位方法

Frequency modulation location method based on dynamic radio

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