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首页> 外文期刊>IEEE transactions on mobile computing >Cooperative Source Node Tracking in Non-Line-of-Sight Environments
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Cooperative Source Node Tracking in Non-Line-of-Sight Environments

机译:非视距环境中的协作源节点跟踪

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The accuracy of localization is highly degraded in indoor and harsh environments where source nodes either do not have connections with a sufficient number of anchor nodes due to strong attenuation or have very poor range estimates due to NLOS propagation. Cooperative localization is a technique in which the source nodes communicate not only with the anchor nodes, but also with each other. Hence, the source nodes can collect several additional measurements which significantly improve the localization performance. Although many studies have examined NLOS-degraded localization of a static node in noncooperative networks, and many others have examined the impact of cooperation for static localization, there is no work which considers cooperative tracking of mobile nodes. To address this open problem, in this work, we examine cooperative tracking, particularly in NLOS environments. More specifically, we develop a novel sensor tracking algorithm based on semidefinite programming (SDP) which has the ability to mitigate NLOS propagation. Our simulations show that the new SDP-based tracking algorithm outperforms the classic extended Kalman filter as well as the other recently proposed algorithms for noncooperative tracking in NLOS environments. We also show that the algorithm can be extended to cooperative networks, and that a substantial performance benefit is realized by cooperation.
机译:在室内和恶劣的环境中,定位的精度会大大降低,在这些环境中,源节点要么由于强衰减而没有与足够数量的锚点节点建立连接,要么由于NLOS传播而导致范围估计很差。合作定位是一种技术,其中源节点不仅与锚节点通信,而且还与彼此通信。因此,源节点可以收集几个额外的测量值,从而显着提高定位性能。尽管许多研究已经研究了非合作网络中NLOS降级的静态节点的本地化,并且许多其他研究已经研究了合作对静态本地化的影响,但是没有工作考虑对移动节点进行合作跟踪。为了解决这个开放性问题,在这项工作中,我们研究了合作跟踪,尤其是在NLOS环境中。更具体地说,我们开发了一种基于半定性编程(SDP)的新型传感器跟踪算法,该算法具有减轻NLOS传播的能力。我们的仿真表明,新的基于SDP的跟踪算法优于经典的扩展​​卡尔曼滤波器以及其他最近提出的NLOS环境中非合作跟踪的算法。我们还表明,该算法可以扩展到协作网络,并且通过协作实现了可观的性能优势。

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