基于UWB的自适应小波与卡尔曼滤波定位算法  

UWB positioning algorithm based on adaptive wavelet transform denouncing and Kalman filtering

作　　者：钟亮 李晓东[1] Zhong Liang;Li Xiaodong(School of Electronic and Information,Xi′an Polytechnic University,Xi′an 710048,China)

机构地区：[1]西安工程大学电子信息学院,西安710048

出　　处：《电子测量技术》2020年第22期165-169,共5页Electronic Measurement Technology

摘　　要：UWB技术由于其较高的测距精度和穿透性能,对于位置服务有着重要的应用价值。在实际的定位环境中,因为受非视距误差和电磁干扰的影响,所以传统的定位算法很难解算出精确的实际位置坐标。传统方法依靠增加基站数量来提高定位精度,但是其成本也在不断提高。针对超宽带定位在干扰较大的室内环境中,定位精度低的问题,提出了一种基于UWB的自适应小波变换去噪与卡尔曼滤波相组合的定位算法,仿真实验验证了该算法大大的减小了定位误差,使定位精度达到厘米级,同时该组合算法与现有的定位解算算法相比可以很好地提高系统的精确性和鲁棒性。UWB technology has important application value for location service due to its high ranging accuracy and penetration performance.In the actual location environment, due to the influence of non-line-of-sight error and electromagnetic interference, it is difficult for the traditional location algorithm to calculate the exact actual location coordinates.The traditional method relies on increasing the number of base stations to improve the positioning accuracy, but its cost is also increasing.disturbance in UWB positioning in large indoor environment, the problem of low positioning accuracy, this paper proposes a adaptive wavelet transform denoising based on UWB positioning algorithm combined with Kalman filter, the simulation experiment shows that this algorithm greatly reduces the positioning error, make the precision of the positioning centimeter level, at the same time the combination algorithm is compared with the existing positioning decoding algorithm can well improve the accuracy and robustness of the system.

关 键 词：超宽带 室内定位 自适应小波变换 卡尔曼滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]