Localization using directional antennas and recursive estimation

M. Nilsson
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引用次数: 8

Abstract

In wireless sensor networks, there is often a need for nodes to find their position. This process is referred to as localization. Many methods have been proposed for this purpose, but they typically suffer from one of two major problems: Either, they are inaccurate for noisy measurement data, or they require a considerable amount of computation. In this paper, we present a method based on recursive estimation of position from angle-of-arrival measurements by directional antennas. The method computes a new position estimate for every new measurement, using a Kalman filter. Computation is fast and is performed entirely locally. No complex data structure needs to be maintained. A prominent feature of the proposed method is that it applies only a linear Kalman filter.
利用定向天线和递归估计进行定位
在无线传感器网络中,经常需要节点找到它们的位置。这个过程被称为本地化。为此提出了许多方法,但它们通常存在两个主要问题之一:要么,它们对有噪声的测量数据不准确,要么需要大量的计算。本文提出了一种基于定向天线到达角测量的位置递归估计方法。该方法使用卡尔曼滤波对每一个新的测量值计算一个新的位置估计。计算速度快,完全在本地执行。不需要维护复杂的数据结构。该方法的一个突出特点是它只应用线性卡尔曼滤波器。
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