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Latency constrained device positioning using a visible light communication two-phase received signal strength - angle of arrival algorithm

机译:使用可见光通信的延迟约束设备定位两相接信号强度 - 到达角度算法

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In positioning systems there is a fundamental tradeoff between accuracy and latency. A latency constrained optimization algorithm is proposed to be employed in conjunction with a prior published two-phase algorithm for estimating the location of a mobile node over the visible light channel. Instead of solely relying on triangulation, the mobile nodes estimate their locations through a two phase algorithm in which they firstly exploit the signal strength observables with unique IDs to establish a coarse estimate, and secondly use the azimuth and elevation observables to establish a fine estimate. In many cases, the fine estimate will improve upon the coarse estimate; however when triangulation fails, the algorithm yields the coarse estimate rather than a localization failure. Since the environment model relies on the primary requirement of adequate illumination, the number of LED anchors, and transmit power for communication functions are determined. The advantage of the two-phase algorithm is that it provides a framework to provide rapid RSS based positional estimates with accuracies bounded to within the illumination projection radius (48 cm median) of the distributed luminaries (anchor nodes) within less than 17 nanoseconds while requiring only a single luminaire in its field of view. However, when there are a sufficient number of luminaires in view the positioning algorithm can further improve the accuracy (14 cm median) through application of triangulation via angle of arrival measurements, at the expense of latency (upto tenths of seconds). The proposed framework allows a fundamental trade of accuracy and latency to be made depending on the observable parameters known to the positioning algorithm at run time.
机译:在定位系统中,精度和延迟之间存在基本的权衡。提出了一种延迟约束优化算法与先前公布的两相算法一起使用,用于估计可见光通道上的移动节点的位置。移动节点而不是仅仅依赖于三角测量,而是通过两相算法估计它们的位置,其中它们首先利用信号强度观察到唯一ID来建立粗略估计,并其次使用方位角和高程观察来建立精细估计。在许多情况下,粗略估计会改善粗略估计;但是,当三角测量发生故障时,算法产生粗略估计而不是本地化故障。由于环境模型依赖于足够的照明的主要要求,因此确定LED锚的数量和用于通信功能的发射功率。两相算法的优点是它提供了一种框架,以便在需要的同时在小于17纳秒内的分布式亮度(锚节节点48cde)内的光学rss的位置估计提供基于快速的RSS的位置估计。只有一个灯具在其视野中。然而,当有足够数量的灯具时,定位算法可以通过通过到达测量角度来进一步提高精度(14cm中位数),以延迟(最多的十分之秒)。所提出的框架允许根据在运行时定位算法已知的可观察参数进行准确性和延迟的基本贸易。

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