标题： 无线传感器网络中的同时定位与地图构建问题 显示英文标题

标题： Simultaneous Localization and Mapping Problem in Wireless Sensor Networks

摘要： 移动设备在无线传感器网络中的定位是一项具有挑战性的任务。 当接入点的WiFi传播图被确定性建模时，这个问题已经得到了解决。 然而，这种过程没有考虑环境动态，并且假设进行离线的人工校准。 在本文中，地图由平均室内传播模型和一个扰动场组成，该扰动场表示环境的影响。 这个扰动场嵌入了一个先验分布。 使用顺序蒙特卡洛方法进行设备定位，并依赖于传播图的估计。 这个推断任务是在线进行的，即使用最近提出的一种基于期望最大化算法的在线方法依次使用观测值。 通过蒙特卡洛实验展示了该算法的性能。 显示英文摘要

摘要： Mobile device localization in wireless sensor networks is a challenging task. It has already been addressed when the WiFI propagation maps of the access points are modeled deterministically. However, this procedure does not take into account the environmental dynamics and also assumes an offline human training calibration. In this paper, the maps are made of an average indoor propagation model combined with a perturbation field which represents the influence of the environment. This perturbation field is embedded with a prior distribution. The device localization is dealt with using Sequential Monte Carlo methods and relies on the estimation of the propagation maps. This inference task is performed online, i.e. using the observations sequentially, with a recently proposed online Expectation Maximization based algorithm. The performance of the algorithm are illustrated through Monte Carlo experiments.