UFO: A United Framework for Target Localization in Wireless Sensor Networks

Jiuyang Tang, Guoming Tang, Daquan Tang, W. Xiao
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Abstract

Recently, various range-free based target localization applications and systems are developed in Wireless Sensor Networks. Nevertheless, few of them can be reused or grafted by others, which has led to serious waste. In this paper, a Unified Framework for target lOcalization (UFO) is proposed and an adaptive grids dividing algorithm is addressed within the framework. Based on the common ground of current typical range-free localization methods, UFO is constructed by four major modules to achieve candidate area acquisition and target location determination: sensor deployment and signal process module, candidate area acquisition module, target localization module and parameter setting module. Not only can UFO construct a localization framework quickly, the computing complexity of loaded localization methods is expected to be decreased by bringing in adaptive grids dividing. In our simulations, the UFO assembled with schemes from node sequences based localization method is tested, and the results from our framework are compared with the original method's. Performance evaluation shows us both UFO and original schemes perform well at localizing accuracy, while the former has a big advantage at real-time capacity.
UFO:无线传感器网络中目标定位的统一框架
近年来,各种基于距离的目标定位应用和系统在无线传感器网络中得到了发展。然而,很少有人可以重复使用或被其他人嫁接,这导致了严重的浪费。提出了一种目标定位的统一框架,并在此框架内研究了自适应网格划分算法。基于当前典型的无距离定位方法的共同点,构建了UFO实现候选区域获取和目标位置确定的四个主要模块:传感器部署与信号处理模块、候选区域获取模块、目标定位模块和参数设置模块。UFO不仅可以快速构建定位框架,而且通过引入自适应网格划分,有望降低加载定位方法的计算复杂度。在仿真中,对基于节点序列定位方法的方案组装的UFO进行了测试,并与原方法的结果进行了比较。性能评估表明,UFO和原始方案在定位精度上都有较好的表现,而原始方案在实时容量上有较大的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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