无线传感器网络的可旋转定向天线定位

Jehn-Ruey Jiang, Chih-Ming Lin, Yi-Jia Hsu
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引用次数: 22

摘要

在本文中,我们展示了一种新的定位方案的设计和实现,称为可旋转天线定位(RAL),用于无线传感器网络(WSN),信标节点具有有规律旋转的定向天线。信标节点周期性地发送包含其位置和天线方向的信标信号。通过观察信标信号的接收信号强度指示(RSSI)值的变化,传感器节点可以估计相对于信标节点的方向。利用两个不同信标节点的估计方向和精确位置,传感器可以计算出自己的位置。提出并实现了传感器节点方位估计的四种方法。其中,我们发现最强信号(SS)方法具有最准确的方向估计。利用SS方法,我们实现了RAL方案,并将其应用于一个10 × 10米室内环境的WSN,该WSN在一侧两端有两个信标节点。实验表明,该方法的平均位置估计误差为76厘米。我们进一步提出了两种方法,即基于网格和基于向量的近似方法,通过安装两个以上的信标节点来改进RAL。仿真结果表明,改进后的定位误差可减小10%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localization with Rotatable Directional Antennas for Wireless Sensor Networks
In this paper we show the design and implementation of a novel localization scheme, called Rotatable Antenna Localization (RAL), for a wireless sensor network (WSN) with beacon nodes with directional antennas which rotate regularly. A beacon node periodically sends beacon signals containing its position and antenna orientations. By observing the variation of the received signal strength indication (RSSI) values of the beacon signals, a sensor node can estimate the orientation relative to the beacon node. With the estimated orientations and exact positions of two distinct beacon nodes, a sensor can calculate its own location. Four methods are proposed and implemented for the sensor node to estimate its orientations. Among them, we find that the strongest-signal (SS) method has the most accurate orientation estimation. With SS method, we implement RAL scheme and apply it to a WSN in a 10- by 10-meter indoor environment with two beacon nodes at two ends of a side. Our experiment demonstrates that the average position estimation error of RAL is 76 centimeters. We further propose two methods, namely grid- and vector-based approximation methods, to improve RAL by installing more than two beacon nodes. We show by simulation that the improvements can reduce about 10% of the position error.
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