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Exploiting Orientation Information to Improve Range-Based Localization Accuracy

机译:利用取向信息以提高基于范围的本地化精度

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This work addresses target localization problem in precarious surroundings where possibly no links are line of sight. It exploits the known architecture of available reference points to act as an irregular antenna array in order to estimate the azimuth angle between a reference point and a target, based on distance estimates withdrawn from integrated received signal strength (RSS) and time of arrival (TOA) observations. These fictitious azimuth angle observations are then used to linearize the measurement models, which triggers effortless derivation of a new estimator in a closed-form. It is shown here that, by using fixed network geometry in which target orientation with respect to a line formed by a pair of anchors can be correctly estimated, the localization performance can be significantly enhanced. The new approach is validated through computer simulations, which corroborate our intuition of profiting from inherent information within a network.
机译:这项工作在可能没有链接的不稳定周围环境中解决了目标本地化问题。它利用了可用参考点的已知架构以充当不规则的天线阵列,以便基于从集成接收的信号强度(RSS)和到达时间(TOA)的距离估计来估计参考点和目标之间的方位角。 )观察。然后,这些虚构的方位角<斜斜视方向角度 <斜体>线性化测量模型,触发以封闭形式的新估计器的轻松推导。这里示出了,通过使用固定网络几何形状,其中可以正确地估计由由一对锚地形成的线的目标取向,可以显着提高本地化性能。通过计算机模拟验证了新方法,这些方法证实了我们从网络内的固有信息中获取利润的直接。

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