基于差分测距的高精度UWB定位算法

High-Precision UWB Positioning Algorithm Based on Differential Ranging

摘要:

针对室内环境存在多种误差,导致超宽带(UWB)定位精度受限、稳定性较弱的问题,提出了基于差分测距的扩展卡尔曼滤波算法(DREKF)。该算法对UWB定位系统的通信协议进行了改进,通过引入差分测距,在每次定位时对各基站的误差模型进行更新,实时校正测距误差,并通过改进的扩展卡尔曼滤波算法对标签进行定位,提升定位精度和稳定性。实验结果表明,DREKF算法在视距情况下的水平定位精度达到了3 cm,在非视距情况下水平定位精度也在4 cm以内,定位精度和稳定性相较于传统的定位算法都有了大幅提升,能够满足高精度室内定位的需求。

Abstract:

A differential ranging-based extended Kalman filter algorithm (DREKF) is proposed to address the limitations in positioning accuracy and weak stability of UWB systems caused by various errors in indoor environ ments. The algorithm improves the communication protocol of the UWB positioning system by introducing differen tial ranging, thus allowing the error model of each base station to be updated during each positioning instance to re duce ranging errors. The improved extended Kalman filter algorithm is applied to locate the tag and thereby enhance both positioning accuracy and stability. Experimental results show that the DREKF algorithm achieves a horizontal positioning accuracy of 3 cm in line-of-sight conditions and 4 cm in non-line-of-sight conditions. Compared with a traditional positioning algorithm, the proposed algorithm significantly improves positioning accuracy and stability, thus satisfying the requirements for high-precision indoor positioning.