Convex programming based robust localization in NLOS prone cluttered environments
Convex programming based robust localization in NLOS prone cluttered environments
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发表时间：
2011-04
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通讯作者：
S. Nawaz;A. Trigoni
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作者：
S. Nawaz;A. Trigoni
在各种工业规模的过程中，固定的或移动的传感器通常部署在大型容器中以监测诸如温度、压力和化学浓度的参数。当这些容器被障碍物（例如，与核废料容器混杂的大型冷却池）杂乱时，传感器越来越难以估计它们的位置。用于估计每个传感器节点与固定到船舶基础设施的参考节点之间的距离的声学测距信号可能遭受非视线（NLOS）信号传播，并且因此在一些估计的距离中引入大的正误差。在本文中，我们提出了一个强大的定位算法定位传感器在杂波NLOS环境。我们表明，如果错误的距离测量的数量小于一半，它是可以准确地估计这些NLOS误差在每个传感器节点通过求解凸优化问题。然后，每个传感器节点可以使用其对NLOS误差的估计来精确地定位自身。我们的方法是完全独立的物理硬件用于执行范围测量，因此可以用来定位传感器节点在任何NLOS倾向的环境。我们证明了这一点的帮助下，实验结果与三个不同的硬件平台，每个采用不同的测距机制。
In a large variety of industrial scale processes, fixed or mobile sensors are typically deployed in large-scale vessels to monitor parameters such as temperature, pressure and chemical concentration. When these vessels are cluttered with obstacles, e.g. large cooling ponds cluttered with nuclear waste containers, it becomes increasingly difficult for the sensors to estimate their position. The acoustic ranging signals used for estimating distances between each sensor node and reference nodes fixed to the vessel infrastructure can suffer from Non-Line-Of-Sight (NLOS) signal propagation and thus introduce large positive errors in some of the estimated distances. In this paper we present a robust localization algorithm for localizing sensors in cluttered NLOS environments. We show that if the number of erroneous range measurements is less than half, it is possible to accurately estimate these NLOS errors at each sensor node by solving a convex optimization problem. Each sensor node can then use its estimate of NLOS errors to accurately localize itself. Our approach is completely independent of the physical hardware used to perform range measurements and thus can be used to localize sensor nodes in any NLOS prone environment. We demonstrate this with the help of experimental results with three different hardware platforms each employing a different ranging mechanism.