基于因子图高斯信念传播的不准确接收机被动定位

W. Yuan, Ganlin Hao, N. Wu, Hua Wang, Jingming Kuang
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引用次数: 1

摘要

位置感知已成为许多实际应用的重要要求。在本文中,我们考虑一个无线网络,其中有一个发射机和多个接收机,他们的目的是定位一个被动目标。现有的被动定位研究假设接收者的位置是完全已知的。然而,在实际情况下,接收器的位置通常是不准确的。针对接收机不准确的被动目标定位问题,提出了一种基于因子图的消息传递算法。将似然函数中的非线性项线性化,求解难解积分。因此,因子图上的所有消息都以高斯封闭形式得到,大大降低了计算复杂度。仿真结果表明,该算法既能准确估计目标位置,又能以较低的复杂度同时确定接收机位置。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Passive localization with inaccurate receivers based on Gaussian belief propagation on factor graph
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.
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