使用具有多个锚点的单个热点的基于超宽带tdoa定位

M. Martalò, G. Ferrari, S. Perri, Gianmichele Verdano, F. D. Mola, Francesco Monica
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引用次数: 4

摘要

在本文中,我们解决了参考节点(锚点)不是分布在目标所在区域的周长,而是集中在一个非常小的区域内,目标在该区域之外的情况下的目标定位问题。此场景在智能建筑应用程序中可能是有意义的,因为锚节点无法在监控区域内分布和布线。另一方面,锚可以安装在单个热点上,放置在感兴趣的环境的中心。在这种情况下,目标必须定位在锚所识别的多面体之外。为此,我们研究了基于超宽带(UWB)的目标定位,并在锚点处进行到达时差(TDoA)处理。对几何优化算法和粒子群优化算法进行了比较分析。结果表明,到达角估计精度较高。此外,粒子群算法虽然保证了更好的性能,但在平均位置估计误差方面,位置估计的“离散度”(即位置误差的标准差)要高于几何算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
UWB TDoA-based Positioning Using a Single Hotspot with Multiple Anchors
In this paper, we address target positioning in scenarios where the reference nodes, denoted as anchors, are not distributed at the perimeter of the area where the target is, but are concentrated in a very small region and target is outside this region. This scenario may be meaningful in smart building applications, where anchor nodes cannot be distributed and cabled in the monitored area. On the other hand, anchors may be installed on a single hotspot to be placed at the center of the environment of interest. In this case, the target has to be localized outside the polytope identified by the anchors. To this end, we investigate Ultra WideBand (UWB)-based target positioning with Time Difference of Arrival (TDoA) processing at the anchors. A comparative analysis between geometric and Particle Swarm Optimization (PSO) algorithms is carried out. Our results show accurate angle of arrival estimation accuracy. Moreover, while PSO guarantees a better performance, in terms of average position estimation error, the “dispersion” of position estimation (i.e., the standard deviation of the position error) is higher than in the case of geometric algorithms.
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