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针对室内实际场景的复杂性，深入分析了室内环境下不同障碍物对超宽带测距精度的影响，并通过控制变量法研究了超宽带穿透障碍物时的入射角、真实距离、穿透介质厚度及其相对介电系数，在此基础上建立了穿透改正模型。结果表明，介质厚度及其相对介电系数是影响超宽带穿透误差的重要因素；穿透改正模型适用于墙体、玻璃和木板，改正后的测距值与真值之差均不超过2 cm；在定位精度要求分米级或米级的室内场景，可忽略玻璃和木板（厚度不超过3 cm）带来的测距误差影响。
Abstract：According to the complexity of indoor scenes, we provided a detailed analysis of the impact of different obstacles on the accuracy of ultra-wideband(UWB) ranging in indoor environments. We used the controlled variable method to analyze the incidence angle, real distance,thickness of penetrating medium and its relative permittivity when UWB signals penetrated obstacles. And then, we established a penetration correction model. The results indicate that the thickness and relative permittivity of medium are significant influence factors. The penetration correction model is applicable to walls, glass, and wooden boards, with the difference between corrected ranging values and true values not exceeding 2 cm. In indoor scenarios where meter or decimeter-level positioning accuracy is required, the influence of UWB ranging errors caused by glass and wooden boards(with thicknesses not exceeding 3 cm) can be disregarded.
[1]刘振耀.基于UWB/GNSS/MIMU的室内外无缝定位技术研究[D].郑州:解放军信息工程大学，2017
[2]景仙林，魏永虎.自回归的卡尔曼滤波算法在UWB定位中的应用[J].地理空间信息，2023,21(5):117-119
[3] Al-Ammar M A,Alhadhrami S,Al-Salman A,et al. Comparative Survey of Indoor Positioning Technologies,Techniques,and Algorithms[C]. IEEE International Conference on Cyberworlds. Santander,Cantabria,Spain,2014:245-252
[4]赵胤植，邹进贵，蔡礼贤，等.一种顾及电子元件延迟的超宽带室内定位方法[J].测绘通报，2022(4):1-5
[5]赵红梅，赵杰磊.超宽带室内定位算法综述[J].电信科学，2018,34(9):130-142
[6]任东宇，任东旭，张元.基于UWB和Skyline的室内三维实时定位技术研究[J].地理空间信息，2017,15(8):113-115
[7]陈燕.基于UWB的高精度室内三维定位技术研究[D].成都:电子科技大学，2018
[8]文铠.基于超宽带的室内定位与定向关键技术研究[D].武汉:武汉大学，2020
[9] Yang X,Wang J,Song D,et al. A Novel NLOS Error Compensation Method Based IMU for UWB Indoor Positioning System[J]. IEEE Sensors Journal,2021,21(9):11 203-11 212
[10] Cui Z,Gao Y,Hu J,et al. LOS/NLOS Identification for Indoor UWB Positioning Based on Morlet Wavelet Transform and Convolutional Neural Networks[J]. IEEE Communications Letters,2020,25(3):879-882
[11] Mao C,Lin K,Yu T,et al. A Probabilistic Learning Approach to UWB Ranging Error Mitigation[C]. IEEE Global Communications Conference(GLOBECOM). Abu Dhabi,United Arab Emirates,2018:1-6
[12]王长强，徐爱功，隋心. UWB测距的NLOS误差削弱方法[J].导航定位学报，2017,5(3):24-27
[13]盛坤鹏，王坚.超宽带NLOS测距误差改正模型[J].北京测绘，2020,34(2):250-254
[14]王川阳，王坚，余航，等.测距误差改正的超宽带定位系统研究[J].测绘科学，2019,44(1):98-103
[15] Wang J,Wang M,Yang D,et al. UWB Positioning Algorithm and Accuracy Evaluation for Different Indoor Scenes[J].International Journal of Image and Data Fusion,2021,12(3):203-225
[16] Zhao Y,Zou J,Guo J,et al. A Novel Ultra-wideband Double Difference Indoor Positioning Method with Additional Baseline Constraint[J]. ISPRS International Journal of Geo-information,2021,10(10):634
[17]贾骏超.超宽带室内定位中NLOS误差抑制方法探讨[J].导航定位学报，2017,5(2):60-64
[18]宰昶丰，郭英，叶瑾，等.基于UWB穿墙定位中NLOS误差的优化方法[J].电子测量技术，2021,44(19):128-133
基本信息:
中图分类号:P207.1;TN925
引用信息:
[1]伍靖雯,邹进贵,周涛,等.室内遮挡环境下超宽带测距误差影响因素分析与改正[J].地理空间信息,2025,23(09):128-132.
基金信息:
国家自然科学基金资助项目（41871373）; 湖北省自然科学基金计划资助项目（2024AFB166）; 湖北省自然资源厅科研计划资助项目（ZRZY2024KJ40）
2025-09-25
2025-09-25