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Combining Kalman Filtering with ZigBee Protocol to Improve Localization in Wireless Sensor Network

机译:结合卡尔曼滤波和ZigBee协议以改善无线传感器网络中的本地化

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We propose a low-cost and low-power-consumption localization scheme for ZigBee-based wireless sensor networks (WSNs). Our design is based on the link quality indicator (LQI)—a standard feature of the ZigBee protocol—for ranging and the ratiometric vector iteration (RVI)—a light-weight distributed algorithm—modified to work with LQI measurements. To improve performance and quality of this system, we propose three main ideas: a cooperative approach, a coefficient delta () to regulate the speed of convergence of the algorithm, and finally the filtering process with the extended Kalman filter. The results of experiment simulations show acceptable localization performance and illustrate the accuracy of this method.
机译:我们为基于ZigBee的无线传感器网络(WSN)提出了一种低成本,低功耗的本地化方案。我们的设计基于链路质量指标(LQI)(ZigBee协议的标准功能),用于测距,而比例矢量迭代(RVI)(一种轻量级分布式算法)经过修改,可用于LQI测量。为了提高该系统的性能和质量,我们提出了三个主要思想:一种协作方法,一个调节算法收敛速度的系数delta(),最后是扩展卡尔曼滤波器的滤波过程。实验仿真结果表明了可接受的定位性能,并说明了该方法的准确性。

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