无指纹跟踪与动态增强的领域划分

Q. Zhang, Ziqiao Zhou, W. Xu, Jing Qi, Chenxi Guo, P. Yi, Ting Zhu, Sheng Xiao
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引用次数: 21

摘要

无线传感器网络常用于跟踪运动物体。许多跟踪算法都有两个一般的假设:预设指纹(先前的地标或上下文信息)和无干扰的环境。然而,这些算法不能用于按需部署,因为指纹是不可用的,并且在干扰多的环境中表现不佳。在本文中,我们提出了一种无指纹定位和跟踪算法,称为增强场划分(EFD)。采用EFD算法,在不留下任何指纹的情况下,动态地将场划分为具有唯一特征的区域,跟踪目标。我们还实现了一个概念验证定位平台,以验证跟踪精度和算法在实际,干扰丰富的环境中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fingerprint-free tracking with dynamic enhanced field division
Wireless sensor networks are often deployed for tracking moving objects. Many tracking algorithms have been proposed with two general assumptions: the preset fingerprints(prior landmark or context information) and an interference-free environment. These algorithms, however, cannot be used for on-demand deployment where finger-prints are unavailable and would perform poorly in interference-rich environments. In this paper, we present a fingerprint-free localizing and tracking algorithm, called Enhanced Field Division (EFD). The EFD algorithm is used to dynamically divide the field into areas with unique signatures and tracks the target, without any finger-prints. We also implemented a proof-of-concept localization platform to demonstrate the tracking accuracy and the algorithm performance in practical, interference rich environment.
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