电讯技术2025，Vol.65Issue(11)：1766-1772,7.DOI:10.20079/j.issn.1001-893x.240530003
一种基于LightGBM的UWB非视距识别方法
A UWB Non-Line-of-Sight Recognition Method Based on LightGBM
摘要
Abstract
For the optimal feature subset selection and model parameter optimization in ultra-wideband non-line-of-sight(NLOS)recognition,a new NLOS recognition method based on the cross-validation recursive feature elimination algorithm of Light Gradient Boosting Machine(LightGBM)and Optuna parameter tuning is proposed.First,six important features,including the difference between the first path signal and the total received signal power,and the maximum noise,are selected as the optimal feature subset using the recursive feature elimination and cross-validation algorithm.Then,Optuna is used to optimize the hyperparameters of LightGBM model.Line-of-sight and non-line-of-sight feature data is collected,and the Support Vector Machine,Extreme Gradient Boosting algorithm,and parameter-optimized LightGBM model are trained and tested.The results demonstrate that the selected features exhibit excellent discriminative ability,with the optimized LightGBM model achieving a recognition accuracy of 95.28%.关键词
超宽带非视距识别/轻量级梯度提升机(LightGBM)/交叉验证递归特征消除算法(RFECV)/超参数优化Key words
UWB NLOS recognition/light gradient boosting machine(LightGBM)/recursive feature elimination with cross validation(RFECV)/hyperparameter optimization分类
电子信息工程引用本文复制引用
李乾,刘卓伦,孙晓云,陈勇,宋士济,张醒龙..一种基于LightGBM的UWB非视距识别方法[J].电讯技术,2025,65(11):1766-1772,7.基金项目
国网河北省电力有限公司石家庄供电分公司项目(SGHESJ00DLJS2401628) （SGHESJ00DLJS2401628）
