Mobile sensor node localization based on sensor fusion using covariance intersection approach

R. Luo, Sung-Sheng Huang, Wei-Lung Hsu
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引用次数: 1

Abstract

A common design of the sensor node is usually not in mobility. The major reason is that long-term motion will cost a lot of energy. But from the other point of view, a mobile sensor node is useful. The accuracy of localization plays an important role for a mobile sensor node. However it is very hard to achieve much highly precise localization for getting a mobile sensor node position data. How to enhance the performance of localization is the most common and important goals. In this paper we used CI (covariance intersection) theory to fuse RSS (received signal strength) and dead-reckoning localization in order to increase the accuracy of localization. Our experiment result shows that the mean distance error is below four percentages. Comparing to RSS and dead-reckoning localization, the accuracy of localization is improved. This paper brings out a reliable algorithm through CI data fusion method to fuse the RSS and dead-reckoning localization estimations.
基于协方差相交法的传感器融合移动传感器节点定位
一般设计的传感器节点通常不具有移动性。主要原因是长时间的运动将消耗大量的能量。但从另一个角度来看,移动传感器节点是有用的。定位精度对移动传感器节点至关重要。然而,获取移动传感器节点位置数据很难实现高精度的定位。如何提高本地化的性能是最普遍也是最重要的目标。为了提高定位精度,本文采用协方差相交(CI)理论将接收信号强度与航位推算定位相融合。实验结果表明,平均距离误差在4%以下。与RSS定位和航位推算定位相比,提高了定位精度。本文通过CI数据融合方法,提出了一种可靠的融合RSS和航位推算定位估计的算法。
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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