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首页> 外文期刊>IEEE Transactions on Communications >TOA-Based Passive Localization Constructed Over Factor Graphs: A Unified Framework
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TOA-Based Passive Localization Constructed Over Factor Graphs: A Unified Framework

机译:基于TOA的被动本地化(基于因子图):一个统一的框架

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摘要

Passive localization based on time of arrival (TOA) measurements is investigated, where the transmitted signal is reflected by a passive target and then received at several distributed receivers. After collecting all measurements at receivers, we can determine the target location. The aim of this paper is to provide a unified factor graph-based framework for passive localization in wireless sensor networks based on TOA measurements. Relying on the linearization of range measurements, we construct a Forney-style factor graph model and conceive the corresponding Gaussian message passing algorithm to obtain the target location. It is shown that the factor graph can be readily modified for handling challenging scenarios such as uncertain receiver positions and link failures. Moreover, a distributed localization method based on consensus-aided operation is proposed for a large-scale resource constrained network operating without a fusion center. Furthermore, we derive the Cramer-Rao bound (CRB) to evaluate the performance of the proposed algorithm. Our simulation results verify the efficiency of the proposed unified approach and of its distributed implementation.
机译:对基于到达时间(TOA)测量的无源定位进行了研究,传输的信号被无源目标反射,然后在几个分布式接收器处接收。在接收器上收集所有测量值之后,我们可以确定目标位置。本文的目的是为基于TOA测量的无线传感器网络中的被动定位提供基于统一因子图的框架。依靠距离测量的线性化,我们构建了一个Forney风格的因子图模型,并构思了相应的高斯消息传递算法来获取目标位置。结果表明,可以轻松修改因子图,以处理挑战性场景,例如不确定的接收器位置和链路故障。此外,针对没有融合中心的大规模资源受限网络,提出了一种基于共识辅助操作的分布式定位方法。此外,我们推导了Cramer-Rao界(CRB)以评估所提出算法的性能。我们的仿真结果验证了所提出的统一方法及其分布式实施的效率。

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