面向室内非视距环境的两阶段超宽带定位算法  

Two-stage Ultra-wideband Positioning Algorithm for Indoor Non-line-of-sight Environments

作　　者：周宁 吴敦 高广 雷少刚[2] ZHOU Ning;WU Dun;GAO Guang;LEI Shaogang(Popsmart Technology(Zhejiang)Company LTD.;School of Environment and Spatial Informatics,China University of Mining and Technology;School of Civil Engineering,NingboTech University)

机构地区：[1]宝略科技(浙江)有限公司 [2]中国矿业大学环境与测绘学院 [3]浙大宁波理工学院土木建筑工程学院

出　　处：《仪表技术与传感器》2025年第3期93-99,共7页Instrument Technique and Sensor

基　　金：宁波市重点研发计划项目(2023Z129,2023Z220);宁波市自然科学基金一般项目(2023J284);宁波市公益性科技计划项目(2023S171);浙江省教育厅一般科研项目(Y202249597)。

摘　　要：针对室内非视距(NLOS)环境下的超宽带定位精度不高的问题,提出了一种包含初始定位和精确定位的两阶段定位算法:初始定位阶段利用改进的低运算成本残差加权算法获得初始位置估计,利用测距残差识别非视距测距,并对非视距基站进行测距重构;精确定位阶段利用LOS/NLOS共同约束域在粒子滤波框架下执行粒子预测,基于减法平均优化算法实现全局寻优获取位置精确估计。室内定位试验结果表明:该算法较标准粒子滤波(PF)算法均方根误差减小41.1%,能在室内非视距环境下有效提高定位精度。Considering the problems associated with low positioning accuracy of ultra-wideband in non-line-of-sight(NLOS)indoor environments,a two-stage positioning algorithm consisting of initial positioning and precise positioning was proposed.The initial positioning stage used an improved low-computational-cost residual weighting algorithm to obtain an initial position estimate,then identified NLOS ranges using residual distance measurements and performed range reconstruction for NLOS base stations.The precise positioning stage used the LOS/NLOS common constraint domain to perform particle prediction within the particle filtering framework and obtained accurate position estimates through global optimization based on a subtraction-average-based optimization algorithm.Indoor positioning experimental results show that the algorithm reduces the positioning error by 41.1%compared to the standard particle filtering algorithm,effectively improving the positioning accuracy in NLOS indoor environments.

关 键 词：室内定位 超宽带 非视距 粒子滤波 残差加权 减法平均优化 

分 类 号：TP301[自动化与计算机技术—计算机系统结构] TN911[自动化与计算机技术—计算机科学与技术]