基于Cayley-menger行列式的基站非视距路径识别方法OA
Non-line-of-sight Path Recognition Based on Cayley-menger Determinant for Base Stations
针对密闭室内环境存在大量非视距路径导致人员定位精度差的问题,提出非视距路径识别算法.构建四元状态假设模型,综合考虑固定基站与移动基站在视距和非视距状态下的情况;利用Cayley-menger行列式的相关定理,建立检验模型识别基站状态;将识别结果作为先验信息求解待定位标签位置.仿真结果表明,所提算法能够准确识别非视距路径,进而应用于定位系统.
Aiming at the problem of poor personnel positioning accuracy caused by numerous non-line-of-sight(NLOS)paths in enclosed indoor environments,a NLOS path recognition algorithm is proposed.A four-state hypothetical model is constructed to comprehensively consider both line-of-sight(LOS)and non-line-of-sight(NLOS)conditions for fixed and mobile base stations.Using the related theorem of Cayley-Menger determinant,a detection model is established to identify the states of base stations.The identification results are used as prior information to estimate the position of the target tag.Simulation results show that the proposed algorithm can accurately identify NLOS paths and can be further applied in positioning systems.
刘宁;寇浩;徐飞虹;杨翠婷;王健安
太原科技大学电子信息工程学院,太原 030024驻太原地区第二军代室,太原 030006北方自动控制技术研究所,太原 030006太原科技大学电子信息工程学院,太原 030024太原科技大学电子信息工程学院,太原 030024
信息技术与安全科学
室内环境非视距识别Cayley-menger行列式状态假设模型标签定位
indoor environmentNLOS identificationCayley-menger determinantstate hypothesis modeltag positioning
《火力与指挥控制》 2026 (5)
59-66,8
山西省科技创新人才团队专项计划(202304051001035)山西省科技成果转化引导专项(202204021301055)山西省专利转化专项计划项目(202302003)山西省留学回国人员科研基金资助项目(2021-133)
评论