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TOA-Based Source Localization: A Linearization Approach Adopting Coordinate System Translation

机译:基于TOA的源本地化:采用坐标系转换的线性化方法

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This paper addresses the localization of a timing signal source based on the time of arrival (TOA) measurements that are collected from nearby sensors that are position known and synchronized to each other. Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). In this paper, we devise a new approach that utilizes linearization and adopts suitable coordinate system translation to eliminate nonlinearity from the converted observation equations. The performance analysis and simulation study conducted show that our proposed algorithm can achieve the CRLB when the zero-mean Gaussian and independent measurement errors are sufficiently small.
机译:本文基于从附近位置已知且彼此同步的传感器收集的到达时间(TOA)测量结果,解决了定时信号源的定位问题。一般而言,对于这种基于TOA的源定位,相应的观测方程式包含测量值与未知参数之间的非线性关系,这通常会导致不存在任何达到Cramer-Rao下界(CRLB)的有效无偏估计量。在本文中,我们设计了一种新方法,该方法利用线性化并采用适当的坐标系平移来消除转换后的观测方程中的非线性。进行的性能分析和仿真研究表明,当零均值高斯和独立的测量误差足够小时,该算法可以实现CRLB。

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