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Error Estimation for the Linearized Auto-Localization Algorithm

机译:线性化自动定位算法的误差估计

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摘要

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method.
机译:线性化自动定位(LAL)算法仅使用到位置未知的移动节点的距离测量值来估计信标节点在本地定位系统(LPS)中的位置。 LAL算法根据线性三边测量方程计算信标间距离,用于信标位置估计。在本文中,我们基于方程的一阶泰勒近似,提出了一种方法,用于估计使用LAL算法获得的信标间距离的误差的传播。由于该方法依赖于这种近似,因此定义了置信度参数τ来测量估计误差的可靠性。现场评估表明,通过将此信息应用于改进的基于加权的自动定位算法(WLAL),相对于原始LAL方法,信标间距离的标准偏差平均可提高30%以上。

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