未知阴影和非视线对可见光室内跟踪的影响

Zafer Vatansever, M. Brandt-Pearce
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引用次数: 9

摘要

随着通信系统和移动设备能力的进步,室内目标跟踪已经引起了人们的兴趣。可见光通信(VLC)是使用发光二极管的射频方法的替代方案。本文将概率滤波算法(粒子滤波和扩展卡尔曼滤波)用于室内跟踪。并将滤波器的性能与另一种定位方法三边定位进行了比较。当非视距分量显著时,概率滤波方法比三边法更可靠。概率滤波算法需要在跟踪之前收集作为指纹图的光强图。随着条件的变化,不可预测的阴影的影响将在其中一个灯被阴影的场景中进行检查。我们的算法以比三边测量更小的误差跟踪用户设备。结果还表明,在高信噪比环境下,算法的跟踪精度与指纹图谱的网格分辨率相当。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of unknown shadowing and non-line-of-sight on indoor tracking using visible light
Indoor target tracking has garnered interest as communication systems and mobile device capabilities advance. Visible light communication (VLC) is an alternative to RF methods that uses light emitting diodes. In this paper, probabilistic filtering algorithms (particle and extended Kalman filters) are used for indoor tracking. The performance of the filters is compared with an another positioning method: trilateration. Probabilistic filtering methods are shown to be more reliable than trilateration for indoor tracking when non-line-of-sight components are significant. The probabilistic filtering algorithms require a light intensity map that is collected as a fingerprint map prior to tracking. The effect of unpredictable shadowing as the conditions change is examined in a scenario where one of the lamps has been shadowed. Our algorithm tracks the user equipment with less error than trilateration. The results also show that the tracking accuracy for our algorithms is on the order of the grid resolution of the fingerprint map for high signal-to-noise ratio environments.
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