Encounter based sensor tracking
Encounter based sensor tracking
复制标题
DOI：
10.1145/2248371.2248377
复制
发表时间：
2012-06
期刊：
影响因子：
--
通讯作者：
A. Symington;A. Trigoni
中科院分区：
文献类型：
--
作者：
A. Symington;A. Trigoni
本文讨论的问题，跟踪一组移动的传感器的环境中，有间歇性的或没有访问的定位服务，如全球定位系统。示例应用包括跟踪地下人员或密集树冠下的动物。我们假设每个传感器使用惯性，视觉或机械里程计来测量其相对运动作为一系列的位移矢量。每个位移矢量遭受少量的误差，该误差复合，导致位置估计的总体精度随时间降低。本文的主要贡献是一种新的离线方法抵消这种错误，利用传感器之间的机会无线电遭遇。我们将遭遇信息与位移向量融合，构建一个模型传感器移动性的图。我们表明，二维传感器跟踪相当于找到一个嵌入这个图在平面上。最后，使用无线电，惯性和地面实况跟踪数据，我们进行模拟，以观察锚的数量，传输范围和无线电噪声如何影响所提出的模型的性能。我们将这些结果与文献中的竞争模型进行了比较。
This paper addresses the problem of tracking a group of mobile sensors in an environment where there is intermittent or no access to a localization service, such as the Global Positioning System. Example applications include tracking personnel underground or animals under dense tree canopies. We assume that each sensor uses inertial, visual or mechanical odometry to measure its relative movement as a series of displacement vectors. Each displacement vector suffers a small quantity of error which compounds, causing the overall accuracy of the positional estimate to decrease with time. The primary contribution of this paper is a novel offline method of counteracting this error by exploiting opportunistic radio encounters between sensors. We fuse encounter information with the displacement vectors to build a graph that models sensor mobility. We show that two dimensional sensor tracking is equivalent to finding an embedding of this graph in the plane. Finally, using radio, inertial and ground truth trace data, we conduct simulations to observe how the number of anchors, transmission range and radio noise affect the performance of the proposed model. We compare these results to those from a competing model in the literature.