物联网应用中大规模无线传感器网络中的高斯-牛顿多重定位算法

Srilakshmi Aouthu, Veeramreddy Jyothsna, Kuraparthi Swaraja, Ravilla Dilli
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引用次数: 0

摘要

传感器节点的位置信息在健康监测、火灾检测和入侵者检测等关键应用中起着重要作用。在传感器节点硬件上安装全球定位系统(GPS)模块并不是了解位置坐标的经济有效的解决方案。这导致了对定义无线传感器网络的新兴定位技术的严格研究。但是,现有的定位技术使用较多的锚节点来计算传感器节点的位置坐标,网络部署成本较高。本文提出了一种低复杂度、基于距离的定位算法,称为高斯-牛顿乘法,该算法使用目标节点接收到的锚节点信号的接收信号强度指标(RSSI)值。该算法仅使用部署在网络地形角落的4个静态锚节点对传感器节点进行定位,定位精度为90.21%上升到98.59%实验结果表明,该算法具有较高的定位精度,适用于大规模无线传感器网络中高精度的传感器节点定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GAUSS-NEWTON MULTILATERATION LOCALIZATION ALGORITHM IN LARGE-SCALE WIRELESS SENSOR NETWORKS FOR IoT APPLICATIONS
The location information of sensor nodes plays an important role in critical applications like health monitoring, fire detection, and intruder detection. Installing global positioning system (GPS) modules with the sensor node hardware is not a cost-effective solution for knowing the location coordinates. This has lead to rigorous research in defining nascent localization techniques for wireless sensor networks. But, the existing localization techniques use more number of anchor nodes to compute the location coordinates of sensor nodes, and the network deployment becomes costly. This article presents a low complex, range-based localization algorithm called gauss-newton multilateration that uses received signal strength indicator (RSSI) values of the anchor nodes' signals received at the target nodes. The proposed algorithm uses only four static anchor nodes, which are deployed at the corners of the network terrain to locate the sensor nodes with localization accuracy of 90.21% and increased up to 98.59%. Based on the results obtained, the proposed algorithm provides higher localization accuracy, and it is well suited for locating sensor nodes with high accuracy in large scale wireless sensor networks.
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