针对室内环境下的非视距(NLOS)传播给定位精度造成较大误差的问题,通过对超宽带(UWB)定位模型进行分析,提出了一种基于全质心-Taylor的混合定位算法.采用对测距误差不敏感的全质心算法将锚点测距数据分组运算,获得目标节点的初始粗定位信息,采用质心修正算法对粗定位节点进行优化运算,从而确定Taylor级数展开初值,再进行迭代求解,进行第二次精细定位.实验结果表明:与Chan-Taylor算法、最小二乘估计(LSE)-Taylor算法相比,本文算法定位精度有明显提高.%A novel full centroid and Taylor cooperative positioning algorithm of ultra wideband(UWB)is proposed aiming at problem of big error of localization precision caused by NLOS propagation in indoor environment.The full centroid positioning algorithm that is not sensitive to localization error is used as the initial rough localization by using anchol point ranging data grouping operations,and then Centroid scheme and selecting the rough localization nodes are applied to coarse localization node preliminary optimization,and the optimized value as the Taylor initial value.Simulation results show that this method has superior positioning precision than Chan-Taylor and LSE-Taylor algorithm.
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