文章基本信息

标题：Augmented Filtering Based on Information Weighted Consensus Fusion for Simultaneous Localization and Tracking via Wireless Sensor Networks
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作者：Xiangyuan Jiang ; Baozhou Lu ; Peng Ren 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/391757
出版社：Hindawi Publishing Corporation
摘要：This paper develops a novel augmented filtering framework based on information weighted consensus fusion, to achieve the simultaneous localization and tracking (SLAT) via wireless sensor networks (WSNs). By integrating augmented transition and observation models, we formulate a dynamical system that encodes both the target moving manners and coarse sensor locations in an augmented state. We then conduct augmented filtering based on augmented extended Kalman filters to estimate the augmented state. We further refine our target estimate according to information weighted consensus filtering which fuses the target information obtained from neighboring sensors. The fused information is fed back as the target estimate to the augmented filter. Our framework is computationally efficient because it only requires neighboring sensor communications. Experiments on SLAT problem validate the effectiveness of the proposed algorithm in terms of tracking accuracy and localization precision in limited ranging conditions.