基于支持向量回归机的RFID室内定位研究

RFID indoor localization based on support vector regression

基于接收信号强度的射频识别(RFID)定位是一种低成本、便于实现的室内定位方法,针对在RFID室内定位系统中使用参考标签法存在的小样本问题,提出一种基于支持向量回归机(SVR)的RFID室内定位算法。结合无源超高频RFID系统工作原理,在Matlab环境下,对比经典的LANDMARC方法,测试了基于支持向量回归机的定位算法性能,以及互耦效应、多径效应对该算法定位结果的影响。仿真结果表明,相较于LANDMARC方法,所提方法在不增加参考标签数量的情况下定位精度至少提高了25%。

Radio frequency identification （RFID） location based on received signal strength is a low cost, easy to implement indoor positioning method. In view of the small sample problem existing in the RFID indoor positioning system when using reference tags, we propose a RFID indoor localization algo- rithm based on support vector regression （SVR）. Combined with the principle of passive ultra high fre- quency RFID system, the performance of the proposed algorithm is tested in MATLAB and then com- pared with that of the classical LANDMARC method. And the influence of mutual coupling effect and multipath effect on the positioning results of the algorithm is also tested. Simulation results show that the proposed method can improve positioning accuracy by at least 25% in comparison with the LAND- MARC method while not increasing the number of reference tags.