Gradient Descent Localization Algorithm Based on Received Signal Strength Technique in a Noisy Wireless Sensor Network

Hussein Hijazi, N. Kandil, N. Zaarour, N. Hakem
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引用次数: 4

Abstract

In this article we propose an improved RSS-based localization technique in a wireless sensor network based on the gradient descent optimization algorithm in a noisy propagation model, usually RSS is susceptible to the noise factor affecting the estimated distance of the sensor network. Generally, to localize an unknown node, a specific number of anchors (reference nodes) is required, this number of needed anchors will increase in the presence of noise factor. Results have shown that, using our improved technique, the number of used anchors is reduced despite the existence of the noise aspect. A comparison with other techniques is made to show the effectiveness of our proposed approach.
噪声无线传感器网络中基于接收信号强度的梯度下降定位算法
本文提出了一种改进的基于梯度下降优化算法的无线传感器网络定位技术。在噪声传播模型中,RSS容易受到噪声因素的影响,影响传感器网络的估计距离。通常,为了定位未知节点,需要一定数量的锚点(参考节点),在存在噪声因子的情况下,锚点的数量会增加。结果表明,使用我们改进的技术,尽管存在噪声方面,但使用的锚的数量减少了。与其他技术的比较表明了我们所提出的方法的有效性。
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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