一种优化的RFID室内定位算法

Indoor positioning algorithm based on RFID technology

射频识别技术已在物流、库存管理等领域广泛应用,但在室内定位应用中仍存在定位精度不高、稳定性差等问题。为了提高定位的精度和稳定性,研究中采用扩展卡尔曼滤波算法、无迹卡尔曼滤波算法以及结合UKF和分段的UKF RTS算法。为了进一步优化RFID定位精度,引入EKF、UKF和UKF RTS算法,UKF方法的最大误差约为0.42 m。但是,UKF RTS的最大精度可以降低到0.26 m左右。UKF RTS算法的误差最小,定位精度相比于EKF算法提高了48%,相比于UKF算法提高了25%。尤其在处理运动状态变化时,UKF RTS表现优异,为RFID室内定位技术的发展提供了新的研究方向。

Radio frequency identification technology has been widely applied in fields such as logistics and inventory management,but there are still problems such as low positioning accuracy and poor stability in indoor positioning applications.In order to improve the ac-curacy and stability of positioning,the extended Kalman Filter algorithm,unscented Kalman Filter algorithm and UKF RTS algorithm combining UKF and Rauch Tung Streebel(RTS)are used in the study.In order to optimize the accuracy of RFID positioning,the EKF,UKF and UKF RTS algorithms are introduced.The maximum error of the UKF method is about 0.42 m.However,the maximum ac-curacy of UKF RTS can be reduced to around 0.26 m.The UKF RTS algorithm has the smallest error and improves positioning accu-racy by 48%compared to the EKF algorithm and 25%compared to the UKF algorithm.Especially when dealing with changes in motion status,UKF RTS performs well and is expected to provide new research directions for the development of RFID indoor positioning technology.