文章基本信息

标题：ERROR MITIGATION ALGORITHM BASED ON BIDIRECTIONAL FITTING METHOD FOR COLLISION AVOIDANCE OF UNMANNED SURFACE VEHICLE
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作者：Lifei Song ; Lifei Song ; Zhuo Chen 等
期刊名称：Polish Maritime Research
电子版ISSN：2083-7429
出版年度：2018
卷号：25
期号：4
页码：13-20
DOI：10.2478/pomr-2018-0127
语种：English
出版社：Sciendo
摘要：Radars and sensors are essential devices for an Unmanned Surface Vehicle (USV) to detect obstacles.Their precision has improved significantly in recent years with relatively accurate capability to locate obstacles.However,small detection errors in the estimation and prediction of trajectories of obstacles may cause serious problems in accuracy,thereby damaging the judgment of USV and affecting the effectiveness of collision avoidance.In this study,the effect of radar errors on the prediction accuracy of obstacle position is studied on the basis of the autoregressive prediction model.The cause of radar error is also analyzed.Subsequently,a bidirectional adaptive filtering algorithm based on polynomial fitting and particle swarm optimization is proposed to eliminate the observed errors in vertical and abscissa coordinates.Then,simulations of obstacle tracking and prediction are carried out,and the results show the validity of the algorithm.Finally,the method is used to simulate the collision avoidance of USV,and the results show the validity and reliability of the algorithm.
关键词：Unmanned Surface Vehicle;Position prediction;Error mitigation;Autoregressive model;Particle Swarm Optimization