RSSI-based Indoor Localization Using RSSI-with-Angle-based Localization Estimation Algorithm

Ambassa Joel Yves, Peng Hao
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引用次数: 16

Abstract

For the scenarios of indoors localization and tracking, the solutions generally need complex infrastructure because they would require either a grid of antennas, each having a well-known position (proximity based approach), or a sophisticated algorithm that uses scene fingerprint to estimate the location or the zone of an object by matching the online measurement with the closest offline measurement. Those techniques may not be available in unknown zones, which will make it difficult to locate a lost node. In this paper, with no additional hardware costs, we propose a new RSSIbased approach in order to find a lost node using a known node. By rotating the known node at the same spot we can collect different RSSI for different polar angles. Two pairs of angles with the strongest RSSI will indicate the main lobes of the radiation pattern, namely, zone of the unknown node. Experimental results illustrate a very close estimation of the unknown node zone, reducing up to 84% of the zone uncertainty.
基于rssi的室内定位与角度定位估计算法
对于室内定位和跟踪的场景,解决方案通常需要复杂的基础设施,因为它们要么需要天线网格,每个天线都有一个已知的位置(基于接近度的方法),要么需要一个复杂的算法,使用场景指纹通过将在线测量与最近的离线测量相匹配来估计物体的位置或区域。这些技术在未知区域可能无法使用,这将使定位丢失节点变得困难。在本文中,在没有额外硬件成本的情况下,我们提出了一种新的基于rssid的方法,以便使用已知节点找到丢失的节点。通过旋转同一点的已知节点,我们可以收集不同极角度的不同RSSI。RSSI最强的两对角度表示辐射方向图的主叶,即未知节点的区域。实验结果表明,对未知节点区域的估计非常接近,减少了高达84%的区域不确定性。
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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