多路径辅助定位的多假设数据关联

M. Ulmschneider, C. Gentner, T. Jost, A. Dammann
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引用次数: 14

摘要

全球卫星导航系统否认在城市峡谷或室内等情况下需要替代的精确定位系统。我们的方法在多路径辅助定位方案中使用地面机会信号。在多路径辅助定位中,到达接收机的每个多路径分量被视为来自虚拟发射机的视距信号。虽然虚拟发射机的位置是未知的,但它们可以使用同时定位和绘图(SLAM)方法同时估计到用户位置。SLAM的一个基本特征是数据关联。本文讨论了多路径辅助定位中的数据关联问题,即识别物理或虚拟发射机之间的对应关系。如果用户识别到先前观察到的发射机,它可以纠正自己的位置估计。我们推广了多路径辅助定位中数据关联的多假设跟踪方案,并通过仿真展示了数据关联如何提高定位精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple hypothesis data association for multipath-assisted positioning
Global navigation satellite system denied scenarios such as urban canyons or indoors cause a need for alternative precise localization systems. Our approach uses terrestrial signals of opportunity in a multipath-assisted positioning scheme. In multipath-assisted positioning, each multipath component arriving at a receiver is treated as a line-of-sight signal from a virtual transmitter. While the locations of the virtual transmitters are unknown, they can be estimated simultaneously to the user position using a simultaneous localization and mapping (SLAM) approach. An essential feature of SLAM is data association. This paper addresses the data association problem in multipath- assisted positioning, i.e., the identification of correspondences among physical or virtual transmitters. If a user recognizes a previously observed transmitter, it can correct its own position estimate. We generalize a previous version of our multiple hypothesis tracking scheme for data association in multipath- assisted positioning and show by means of simulations how data association improves the positioning accuracy.
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