We present a message passing algorithm for localization and tracking in multipath-prone environments that implicitly considers obstructed line-of-sight situations. The proposed adaptive probabilistic data association algorithm infers the position of a mobile agent using multiple anchors by utilizing delay and amplitude of the multipath components (MPCs) as well as their respective uncertainties. By employing a nonuniform clutter model, we enable the algorithm to facilitate the position information contained in the MPCs to support the estimation of the agent position without exact knowledge about the environment geometry. Our algorithm adapts in an online manner to both, the time-varying signal-to-noise-ratio and line-of-sight (LOS) existence probability of each anchor. In a numerical analysis we show that the algorithm is able to operate reliably in environments characterized by strong multipath propagation, even if a temporary obstruction of all anchors occurs simultaneously.
翻译:我们提出了一个信息传递算法,用于在多病易发环境中进行定位和跟踪,这种算法含蓄地考虑到阻碍的视线情况。拟议的适应性概率数据联系算法通过利用多病组分的延迟和振幅以及各自的不确定性,推断了使用多个锚的移动剂的位置。我们采用非统一散变模型,使算法能够促进多病易发环境中的定位信息,以支持在不确切了解环境几何学的情况下估计代理人的位置。我们的算法以在线方式调整了每个锚同时存在的时间变化信号到噪音坐标和视线概率。在一项数字分析中,我们显示算法能够在以强烈多病传播为特征的环境中可靠地运作,即使所有锚同时出现临时障碍。