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Simultaneous localization and mapping in indoor positioning systems based on round trip time-of-flight measurements and inertial navigation

机译:基于往返飞行时间测量和惯性导航的室内定位系统中的同时定位和地图绘制

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This paper describes the algorithm for positioning of both indoor base stations and pedestrians in nanoLOC (IEEE 802.15.4a) wireless network. The algorithm uses three sources of information: time-of-flight ranging results between a mobile tag and base stations, the trajectory obtained from an embedded inertial measurement unit, and the map of the building. The iterative algorithm consists of two consequent interconnected stages. The particle filter is used to localize the mobile object on the map, whereas the discrete Bayes filter (grid filter) is applied for estimating the positions of base stations. Time-of-flight non-line-of-sight error distribution function was used as a likelihood in the discrete Bayes filter. Simulation shows that the described SLAM algorithm can be effectively used for setting the initial positions of base stations on the predefined map to save the installation time without significant decrease of localization accuracy. The proposed technique was applied in RealTrac local positioning technology.
机译:本文介绍了在nanoLOC(IEEE 802.15.4a)无线网络中定位室内基站和行人的算法。该算法使用三种信息源:移动标签和基站之间的飞行时间测距结果,从嵌入式惯性测量单元获得的轨迹以及建筑物地图。迭代算法由两个随后的互连阶段组成。粒子滤波器用于在地图上定位移动对象,而离散贝叶斯滤波器(网格滤波器)用于估计基站的位置。飞行时间非视距误差分布函数在离散贝叶斯滤波器中用作可能性。仿真表明,所描述的SLAM算法可以有效地用于在预定义的地图上设置基站的初始位置,从而节省安装时间,而不会显着降低定位精度。所提出的技术已应用于RealTrac本地定位技术中。

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