非视线传播
计算机科学
测距
卡尔曼滤波器
鉴定(生物学)
加速度计
超宽带
无线
人工智能
电信
植物
生物
操作系统
作者
Wang Qiu,Ming-Song Chen,Guan-Qiang Wang,Kai Li,Y.C. Lin,Z. Li,Chizhou Zhang
标识
DOI:10.1109/lcomm.2023.3340248
摘要
In this letter, we propose a novel Non-Line-of-Sight (NLOS) identification and error-mitigation method for dynamic object positioning and ultra-wideband (UWB) ranging. By utilizing inverse estimation on known Anchor Points (APs) and improved robust unscented Kalman filter (IRUKF), while fusing Gyroscope and Accelerometer data, the proposed technology identifies and compensates for NLOS occlusions between tag and APs, reducing positioning errors. The approach has been verified through simulation and experiment, with identification precision of 97.02%. After mitigating errors, substantial error reductions of 91.80% and 98.90% were observed in LOS and NLOS situations, respectively. Moreover, the developed IRUKF effectively minimizes mislocalization by 50.48% in harsh scenarios.
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