Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements
Accurate Pedestrian Indoor Navigation by Tightly Coupling Foot-Mounted IMU and RFID Measurements
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DOI：
10.1109/tim.2011.2159317
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发表时间：
2012-01-01
影响因子：
5.6
通讯作者：
Guevara Rosas, Jorge I.
中科院分区：
文献类型：
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作者：
Jimenez Ruiz, Antonio Ramon;Seco Granja, Fernando;Guevara Rosas, Jorge I.
提出了一种将惯性导航系统（INS）技术与有源RFID技术相融合的室内人员精确定位新方法。一种基于脚装式惯性测量单元（伊穆斯）的位置估计方法，由从放置在建筑物中的已知位置处的若干有源RFID标签获得的接收信号强度（RSS）辅助。与其他作者集成伊穆斯和RSS与松散的卡尔曼滤波器（KF）为基础的耦合（通过使用惯性和RSS计算的位置的残差）相比，我们提出了一个紧密的基于KF的INS/RFID集成，使用INS预测的读取器到标签的范围和从通用RSS路径损耗模型导出的范围之间的残差。我们的方法还包括其他漂移减少方法，如零速度更新（ZUPT）在脚站姿检测，零角速率更新（ZARU）时，用户是不动的，和使用磁力计的航向校正。一个互补的扩展卡尔曼滤波器（EKF），在其15个元素的误差状态向量，补偿的位置，速度和姿态误差的INS解决方案，以及IMU的偏差。该方法对于任何类型的运动（以不同的速度向前、侧向或向后行走）都是有效的，并且不需要对用户步态进行离线校准。集成的INS+RFID方法消除了单独IMU解决方案的典型漂移（约占总行驶距离的1%），导致沿步行路径（无论其长度如何）的典型定位误差沿着约1.5 m。
We present a new method to accurately locate persons indoors by fusing inertial navigation system (INS) techniques with active RFID technology. A foot-mounted inertial measuring units (IMUs)-based position estimation method, is aided by the received signal strengths (RSSs) obtained from several active RFID tags placed at known locations in a building. In contrast to other authors that integrate IMUs and RSS with a loose Kalman filter (KF)-based coupling (by using the residuals of inertial- and RSS-calculated positions), we present a tight KF-based INS/RFID integration, using the residuals between the INS-predicted reader-to-tag ranges and the ranges derived from a generic RSS path-loss model. Our approach also includes other drift reduction methods such as zero velocity updates (ZUPTs) at foot stance detections, zero angular-rate updates (ZARUs) when the user is motionless, and heading corrections using magnetometers. A complementary extended Kalman filter (EKF), throughout its 15-element error state vector, compensates the position, velocity and attitude errors of the INS solution, as well as IMU biases. This methodology is valid for any kind of motion (forward, lateral or backward walk, at different speeds), and does not require an offline calibration for the user gait. The integrated INS+RFID methodology eliminates the typical drift of IMU-alone solutions (approximately 1% of the total traveled distance), resulting in typical positioning errors along the walking path (no matter its length) of approximately 1.5 m.