物联网学报2023，Vol.7Issue(4)：63-71,9.DOI:10.11959/j.issn.2096-3750.2023.00348
一种行人遮挡下的UWB非视距传播识别方法
A UWB NLOS identification method under pedestrian occlusion
摘要
Abstract
Ultrawideband(UWB)is a hot technology for indoor positioning with large bandwidth,strong an-ti-interference ability,and high multipath resolution capacity.However,due to the complex indoor environment,UWB signal propagation will inevitably be blocked,resulting in non-line-of-sight(NLOS)propagation,which greatly reduces the accuracy of UWB positioning.Therefore,identifying NLOS signals accurately and discarding or correcting them are important to alleviate the problem of the decline in positioning accuracy.The majority of present NLOS identification work focuses on scenes with building structures such as walls.Further discussion is needed for scenes obscured by pe-destrians.Since the impact of human obstacles on the signals is more complex and cannot be ignored,the NLOS identifi-cation under pedestrian occlusion was studied.By comparing a variety of machine learning methods and signal feature combinations,the random forest method based on the three-dimensional features of the first path signal power,the re-ceived signal power,and the measured distance was proposed.These features with fewer dimensions and easy extraction were used to achieve a high identification percentage for NLOS.The experimental results based on the measured data of different devices show that the NLOS identification accuracy based on the proposed method reaches 99.05%,99.32%and 98.81%respectively.关键词
UWB/室内定位/非视距识别/随机森林Key words
UWB/indoor positioning/NLOS identification/random forest分类
信息技术与安全科学引用本文复制引用
吴彤,李业深,黄镇煌,张煜,张万乐,熊轲..一种行人遮挡下的UWB非视距传播识别方法[J].物联网学报,2023,7(4):63-71,9.基金项目
中央高校基本科研业务费项目(No.2022JBGP003) （No.2022JBGP003）
国家自然科学基金资助项目(No.62071033) （No.62071033）
国家重点研发计划(No.2020YFB1806903)The Fundamental Research Funds for the Central Universities(No.2022JBGP003),The National Natural Science Foundation of China(No.62071033),The National Key Research and Development Program of China(No.2020YFB1806903) （No.2020YFB1806903）
