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Passive localization with inaccurate receivers based on Gaussian belief propagation on factor graph

机译:基于因子图上高斯置信度传播的不精确接收器的被动定位

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摘要

Location awareness is now becoming vital requirement for many practical applications. In this paper, we consider a wireless network where there is one transmitter and multiple receivers and they aim to locate a passive target. Existing studies on passive localization assume receivers' positions are perfectly known. However, receivers' positions are generally inaccurate in actual scenarios. A factor graph based message passing algorithm is proposed to locate the passive target with inaccurate receivers. The nonlinear term in likelihood function is linearized to solve the intractable integrals. Accordingly, all messages on factor graph are obtained in Gaussian closed forms which reduce the computational complexity significantly. Simulation results show the proposed algorithm can not only estimate the target's position accurately but also determine the receivers' positions simultaneously with low complexity.
机译:现在,位置感知已成为许多实际应用中的重要要求。在本文中,我们考虑一个无线网络,其中有一个发射器和多个接收器,它们旨在定位无源目标。现有的关于被动定位的研究假设接收器的位置是众所周知的。但是,在实际情况下,接收器的位置通常不准确。提出了一种基于因子图的消息传递算法,用于对接收方不准确的被动目标进行定位。似然函数中的非线性项被线性化以解决不可积分。因此,因子图上的所有消息均以高斯封闭形式获得,这大大降低了计算复杂度。仿真结果表明,该算法不仅能够准确估计目标位置,而且能够以较低的复杂度同时确定接收者的位置。

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