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Closed-form solution for TDOA-based joint source and sensor localization in two-dimensional space

机译:二维空间中基于TDOA的联合源和传感器定位的封闭式解决方案

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摘要

In this paper, we propose a closed-form solution for time-difference-of-arrival (TDOA) based joint source and sensor localization in two-dimensional space (2D). This closed-form solution is a combination of two closed-form solutions for time-of-arrival information recovery and time-of-arrival (TOA)-based joint source and sensor localization in 2D. In our previous works, we derived closed-form solutions for TOA-based joint source and sensor localization and near-closed-form solutions for TOA information recovery in three-dimensional space (3D). Since the localization in 2D is simpler than that in 3D, closed-form solutions for both problems in 2D are derived in this paper. The root-mean-square errors (RMSEs) achieved by the proposed closed-form solution are compared with the Cramér-Rao lower bound (CRLB) in synthetic experiments. The results show that the proposed solution works well in both low-noise and noisy cases and with both small and large numbers of sources and sensors.
机译:在本文中,我们针对二维空间(2D)中基于到达时间差(TDOA)的联合源和传感器定位提出了一种封闭形式的解决方案。此封闭式解决方案是两个封闭式解决方案的组合,用于到达时间信息恢复以及基于到达时间(TOA)的2D联合源和传感器定位。在我们之前的工作中,我们导出了基于TOA的联合源和传感器定位的封闭式解决方案,以及用于三维空间(3D)中TOA信息恢复的近似封闭式解决方案。由于2D中的定位比3D中的定位更简单,因此本文针对2D中的两个问题导出了封闭形式的解决方案。通过拟议的封闭形式解决方案获得的均方根误差(RMSE)与合成实验中的Cramér-Rao下界(CRLB)进行了比较。结果表明,所提出的解决方案在低噪声和高噪声情况下均适用,并且无论源和传感器的数量如何都很大。

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