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。
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.
出处
《计算机工程》
CAS
CSCD
2013年第11期91-95,共5页
Computer Engineering
基金
国家自然科学基金资助项目(61100210)
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
Received Signal Strength Indicator（RSSI）
Inertial Measurement
wireless sensor
extended Kalman filtering
adaptive steplength
