基于多元线性回归的距离定位算法评价准则设计

Dhouha El Houssaini, Zaid Abdullah, Sabrine Kheriji, K. Besbes, O. Kanoun
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引用次数: 2

摘要

定位是许多无线传感器网络(WSN)应用的基本特征,包括跟踪、健康监测和军事监督。定位系统的分析建模和分析仍然具有挑战性和不可行的,因为它提供的结果过于简化,对评估案例的可靠性有限。同样,试验台的推广也涉及大量的工作,使得仿真阶段成为研究无线传感器网络定位不可或缺的环节。所定义的定位模型需要在仿真过程中保证可靠和实用的网络假设。然而,大多数网络模拟器不满足与网络定义相关的特定标准,例如可伸缩性和异构性。在此基础上,提出了一套基于距离的定位技术方法评价与分析准则。采用多元线性回归生成不同的定位实例,支持不同且不相关的参数。开发的基于距离的定位准则在现有的定位中进行了测试和验证
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Guideline for Range-based Localization Algorithms Evaluation using Multiple Linear Regressions
Localization is an essential feature in numerous Wireless Sensor Network (WSN) applications, including tracking, health monitoring, and military supervision. Analytical modeling and analysis of the localization system remain challenging and infeasible since it offers oversimplified results with limited reliability to the evaluated cases. Likewise, disseminating test-beds involves a lot of effort, making the simulation phase indispensable to study the WSN localization. The defined localization model needs to ensure solid and pragmatic network assumptions during the simulation. However, most network simulators don’t meet specific criteria related to network definition, such as scalability and heterogeneity. As part of this endeavor, a guideline for evaluating and analyzing technical methods of range-based localization is developed. Multiple linear regression is used to generate the different localization instances, which enables to support different and non-dependent parameters. The developed guideline for range-based localization is tested and validated for existing localization
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