文章基本信息

标题：Bearing-only AUV tracking performance: Unscented Kalman Filter estimation against uncertainty in underwater nodes position
本地全文：下载
作者：Riccardo Costanzi ; Davide Fenucci ; Vincenzo Manzari 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：13674-13679
DOI：10.1016/j.ifacol.2017.08.2530
语种：English
出版社：Elsevier
摘要：AbstractAutonomous Underwater Vehicles require highly accurate autonomous navigation to achieve long-term tasks while collecting data that need to be correctly georeferenced. Nevertheless, no standard evaluation methods for vehicle navigation skills exist, and therefore we aim to design a bearing-only based underwater test range to accomplish that. A previous work identified some unavoidable issues in marine applications that imply uncertainty in knowledge of actual network nodes positions, and the resulting possible invalidation of the Extended Kalman Filter performance. The main goal of this paper is to highlight the results obtainable applying the Unscented Kalman Filter to mitigate this sensor positions perturbation effect. The analysis of the simulative results discussed in this paper confirms the possibility to counteract the realistic uncertainty in sensor positions with the proposed filter, which may be the right candidate for on-board implementation.
关键词：KeywordsBearings only trackingrobot navigationnavigation systemsaccuracytarget trackingmarine systems