本文设计了一种基于联邦卡尔曼滤波的WLAN系统与RFID系统联合定位的信息融合算法。针对室内移动节点单一定位系统存在的定位精度不够、定位时间过长及算法复杂度不理想等问题,提出将WLAN系统和RFID系统作为联邦滤波器的两个独立子系统,采用无迹卡尔曼滤波算法进行独立的量测更新和时间更新,主滤波器用无反馈模式对子系统输出的信息进行融合。仿真结果表明,该算法分散和减少了无迹卡尔曼滤波的计算量,较之于单一定位系统,大幅减少了最大偏差和最小偏差,定位精度显著改善。 In this paper, an information fusion algorithm based on federated Kalman filtering for WLAN and RFID systems is proposed. Aiming at the problems such as the lack of positioning accuracy, long positioning time and poor algorithm complexity of indoor mobile node single location system, WLAN system and RFID system are proposed as two independent subsystems of federated filter. Unscented Kalman filter The algorithm performs independent measurement update and time update, and the main filter integrates the information output by the subsystems in a feedback-free mode. The simulation results show that the proposed algorithm disperses and reduces the computational complexity of unscented Kalman filter, greatly reduces the maximum deviation and the minimum deviation compared with a single positioning system, and the positioning accuracy is significantly improved.