计算机工程

• 移动互联与通信技术 • 上一篇    下一篇

基于RSSI与惯性测量的室内定位系统

胡伟娅,陆佳亮,伍民友   

  1. (上海交通大学计算机科学与工程系,上海 200240)
  • 收稿日期:2012-10-26 出版日期:2013-11-15 发布日期:2013-11-13
  • 作者简介:胡伟娅(1988-),女,硕士,主研方向:无线传感器网络;陆佳亮,讲师、博士;伍民友,教授、博士生导师、CCF高级会员
  • 基金项目:
    国家自然科学基金资助项目(61100210)

Indoor Positioning System Based on RSSI and Inertial Measurement

HU Wei-ya, LU Jia-liang, WU Min-you   

  1. (Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai 200240, China)
  • Received:2012-10-26 Online:2013-11-15 Published:2013-11-13

摘要: 介绍融合接收信号强度指示(RSSI)和惯性测量技术的无线传感器室内定位系统,该系统通过可穿戴式无线传感器节点和环境辅助传感器节点,采集步行者的位置信息。可穿戴式节点采用Dead Reckoning惯性测量方法,存在累积误差,可通过在室内环境中布置RSSI节点矫正步行者的位置信息。采用扩展性的卡尔曼滤波算法将惯性测量与RSSI测量数据相结合,实现自适应的步长算法,较大程度改进步长不正确读取带来的误差。实验结果表明,与纯粹的惯性测量系统相比,该系统能提高66.3%的精确度。

关键词: 接收信号强度指示, 惯性测量, 无线传感器, 扩展性的卡尔曼滤波, 自适应步长

Abstract: This paper introduces a wireless sensor tracking system for personal indoor positioning based on Received Signal Strength Indicator(RSSI) and Dead Reckoning(DR) technology. The system is built with portable on-body sensor nodes and assisted sensor nodes deployed in the targeted indoor area. It takes a hybrid approach with pedestrian dead reckoning and radio-based localization. Real-time inertial measurements are combined with RSSI-based information, and processed with an extended Kalman filtering to be weighted in the location estimation according to their reliability. It incorporates with an adaptive step length algorithm to reduce the deviation of the measurements. Experimental results show that the system can improve the accuracy of the positioning by 66.3% compared with pure inertial dead reckoning system.

Key words: Received Signal Strength Indicator(RSSI), Inertial Measurement, wireless sensor, extended Kalman filtering, adaptive step length

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