AWCL:自适应加权质心定位作为粗粒度定位的有效改进

R. Behnke, D. Timmermann
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引用次数: 80

摘要

传感器节点的定位是无线传感器网络中的关键问题之一。它是各种场景以及地理集群和路由的先决条件。粗粒度定位的一种简单方法是加权质心定位(WCL),不幸的是,这种方法有一些缺点。因此,我们提出了在精度方面优于线性加权WCL的“自适应WCL”(AWCL)算法。此外,AWCL使用二次权值实现了与WCL相似的精度,但不依赖于二次WCL那样复杂的计算。AWCL的自适应特性使得信标通信范围的定位失败很小,甚至超过信标距离。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AWCL: Adaptive Weighted Centroid Localization as an efficient improvement of coarse grained localization
Localization of sensor nodes is one of the key issues in wireless sensor networks. It is a precondition for a variety of scenarios as well as geographic clustering and routing. A simple approach for coarse grained localization is weighted centroid localization (WCL), which, unfortunately, comes with some drawbacks. Therefore, we present the "Adaptive WCL" (AWCL) algorithm that outperforms the linearly weighted WCL in terms of accuracy. Moreover, AWCL achieves similar accuracy as WCL using quadratic weights, but does not rely on complex calculations like quadratic WCL. The adaptive character of AWCL leads to a small localization failure for beacon communication ranges, exceeding the beacon distance.
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