摘要
本文基于Chan算法的UWB室内定位算法进行改进,在原有基础上使用卡尔曼滤波优化并提出了根据残差值变化,不断更新卡尔曼滤波模型中测量误差R和过程误差以取代Q,取代原有模型中经验值,从而提高算法的定位精度。实验结果表明,本文算法优于传统的Chan-TDOA定位算法。
This paper aims at UWB indoor location algorithm based on Chan algorithm,On the basis of the original optimization,kalman filter is used,and according to the change of residual value,the measurement error R and process error in kalman filter model are constantly updated to replace Q and the experience value in the original model,so as to improve the positioning accuracy of the algorithm.The experimental results show that the proposed algorithm is superior to the traditional Chan-TDOA localization algorithm.
作者
柏雨晨
BAI Yuchen(Beijing Wuzi University,Beijing 101149,China)
出处
《信息与电脑》
2021年第20期16-18,共3页
Information & Computer
基金
北京市教委科技计划一般项目(项目编号:KM201910037001,KM201910037186)。
作者简介
柏雨晨(1997-),男,北京人,硕士研究生。研究方向:智能物流系统。
