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Complex Multidimensional Scaling Algorithm for Time-of-Arrival-Based Mobile Location: A Unified Framework

机译:基于到达时间的移动位置的复杂多维缩放算法:统一框架

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Localization of mobile station (MS) is a very popular research topic at present. In this study, a novel complex framework of multidimensional scaling (MDS) algorithm for positioning a stationary target is introduced by utilizing time-of-arrival measurements collected by passive base stations (BSs). The complex MDS framework is based on the transformation of complex coordinates extending the dimension of noise subspace for positioning and strengthening the constraints between BSs and MS. Computer simulations are included to verify the development and to contrast the estimator performance with their corresponding real versions as well as the Cram,r-Rao lower bound. It is shown that each complex method has lower mean square position errors and more robust than its real version.
机译:移动站(MS)的本地化是当前非常流行的研究主题。在这项研究中,通过利用无源基站(BS)收集的到达时间测量值,介绍了用于定位固定目标的新型多维缩放(MDS)复杂算法框架。复杂的MDS框架基于复杂坐标的转换,扩展了噪声子空间的维度,用于定位和加强BS与MS之间的约束。包括计算机仿真程序以验证开发情况,并将估算器性能与其相应的实际版本以及Cram,r-Rao下限进行对比。结果表明,每种复杂方法均比其实际方法具有更低的均方位置误差和更强的鲁棒性。

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