基于动态加权的多源融合定位算法

Multi-source fusion localization algorithm based on dynamic weighting

针对单一信号源的室内定位方法难以获取到稳定和高精度定位结果的问题,提出一种多源信息融合定位的方法,来得到高可用的定位结果;该方法首先对WIFI指纹定位、蓝牙三边测量定位和RFID近邻法定位进行动态加权,得到绝对位置;然后与行人航迹推算得到的位置用卡尔曼滤波融合得到最后的定位结果。实验表明,该算法对定位效果改善明显,定位精度达到亚米级。

The indoor positioning method for a single signal source is difficult to obtain stable and high-precision positioning results. A multi-source information fusion positioning method is proposed to obtain highly available positioning results. The method first dynamically weights WIFI fingerprint positioning, Bluetooth trilateration positioning and RFID neighbor positioning, and obtains an absolute position. Then, the wireless positioning position and the position calculated by the pedestrian track are combined by Kalman filter to obtain the final positioning result. Experiments show that this algorithm improves the positioning effect obviously, and the positioning accuracy reaches the sub-meter level.