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Use of frequency diversity to improve the performance of RSSI-based distance measurements

机译:使用频率分集来提高基于RSSI的距离测量的性能

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In several fields of application of wireless sensors networks (WSNs) the ability of estimating the position of a node with respect to a reference coordinate is a key feature. The most of the WSN applications involve indoor environments and low costs requirements, so the Global Position System cannot always assure a reliable operating and cheap solution. As a consequence, other methods have to be considered for nodes locating, among all, the most widespread methods are based on Received Signal Strength Indicator (RSSI) measurements. The main advantage of this method is that it does not require additional hardware since the measurement of RSSI is often built-in in radio chipsets for the most common standards in use for a WSN (Bluetooth, Wi-Fi, ZigBee). However, solutions based on RSSI measurements suffer of high uncertainty due to several phenomena as high variability of RSSI measurements, external interferences and multipath to cite a few. In this paper the influence of the multipath is investigated and the effects of different processing techniques for multipath mitigating, based on the employment of frequency diversity, are analyzed in simulation environment and in real scenarios.
机译:在无线传感器网络(WSN)的几个应用领域中,估计节点相对于参考坐标的位置的能力是关键特征。 WSN的大多数应用都涉及室内环境和低成本要求,因此,全球定位系统无法始终确保可靠的运行和廉价的解决方案。结果,必须考虑其他方法来进行节点定位,其中,最普遍的方法是基于接收信号强度指示器(RSSI)的测量。该方法的主要优点在于,它不需要额外的硬件,因为RSSI的测量通常内置在无线芯片组中,以用于WSN(蓝牙,Wi-Fi,ZigBee)的最常用标准。但是,基于RSSI测量的解决方案由于诸如RSSI测量的高度可变性,外部干扰和多径引用等多种现象而具有较高的不确定性。本文研究了多径的影响,并基于频率分集的使用,在仿真环境和实际场景中分析了不同处理技术对多径缓解的影响。

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