吉林大学学报（信息科学版）2024，Vol.42Issue(2)：193-199,7.
信号干扰下的超宽带精确定位问题研究
Research on Precise Positioning of Ultra Wide Band with Signal Interference
摘要
Abstract
In the field of indoor applications of UWB(Ultra Wide Band)positioning technology,it is important to establish an efficient and accurate 3D coordinate positioning system to overcome signal interference.Machine learning methods are used to investigate the problem of accurate positioning of indoor UWB signals under interference.Firstly,various statistical analysis models are used to clean up invalid or error measurements,then the a priori knowledge of TOF(Time Of Flight)algorithm is combined with neural network and XGBoost algorithm to build a neural XGB(Exterme Gradient Boosting)3D oriented system.The system can accurately predict the coordinate value of the target point by"normal data"and"abnormal data"(disturbed),the coordinates of four anchor points,and the final error is as low as 5.08 cm in two-dimensional plane and 8.03 cm in three-dimensional space.A neural network classification system is established to determine whether the data is disturbed or not,with an accuracy of 0.88.Finally,by combining the above systems,continuous and regular motion trajectories are obtained,which proves the effectiveness and robustness of the systems.关键词
UWB精准定位/神经网络/XGBoost算法/逻辑回归Key words
ultra wide band(UWB)precision positioning/neural network/XGBoost algorithm/logistic regression分类
信息技术与安全科学引用本文复制引用
张爱琳,刘辉,王小海,张秀伊,邱正中,吴春国..信号干扰下的超宽带精确定位问题研究[J].吉林大学学报（信息科学版）,2024,42(2):193-199,7.基金项目
吉林省科技发展计划基金资助项目(20230201083GX) （20230201083GX）
