GPS-free cooperative mobile tracking with the application in vehicular networks

Arghavan Amini, R. Vaghefi, J. M. Garza, R. Buehrer
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引用次数: 13

Abstract

In this paper, the problem of mobile tracking in dense environments is studied. The Global Positioning System (GPS) is the most accessible positioning technique. However, GPS does not work properly in indoor and dense areas, as the receiver typically does not have access to a sufficient number of line-of-sight satellites. Therefore, localization in these networks can be alternatively done by using measurements collected within the network and without the aid of any external resources (e.g., GPS). The mobile tracking problem includes several static reference nodes whose locations are fixed and known, and many mobile nodes whose locations are unknown and needed to be determined. The problem of mobile tracking can be solved in two forms: centralized and distributed. A centralized algorithm can result in high complexity and latency, while a distributed algorithm might lead to large estimation errors. In this paper, a novel cooperative localization technique is introduced which is able to deliver a promising localization accuracy while maintain the latency and complexity as low as possible. The performance of the proposed algorithm is compared with those of other algorithms in terms of localization accuracy, latency, and required data communication through computer simulations. The simulation results show the effectiveness of the proposed algorithm in comparison with either centralized and distributed algorithms. An important application of this work is vehicle localization in dense environments where the vehicles do not have access to GPS satellites and must be localized by the elements within the network.
无gps协同移动跟踪在车载网络中的应用
本文研究了密集环境下的移动跟踪问题。全球定位系统(GPS)是最容易使用的定位技术。然而,GPS不能在室内和密集区域正常工作,因为接收器通常无法访问足够数量的视距卫星。因此,在这些网络中的定位可以通过使用网络内收集的测量数据而不借助任何外部资源(例如GPS)来完成。移动跟踪问题包括几个位置固定且已知的静态参考节点和许多位置未知且需要确定的移动节点。移动跟踪问题的解决有集中式和分布式两种形式。集中式算法可能导致较高的复杂性和延迟,而分布式算法可能导致较大的估计误差。本文提出了一种新的协同定位技术,该技术在保证较低的定位延迟和复杂性的同时,能够提供较高的定位精度。通过计算机仿真,比较了该算法在定位精度、时延和所需的数据通信等方面与其他算法的性能。仿真结果表明了该算法与集中式和分布式算法的有效性。这项工作的一个重要应用是在密集环境下的车辆定位,在这种环境下,车辆无法访问GPS卫星,必须通过网络中的元素进行定位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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