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《Optics and Precision Engineering》 2019-04
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Shiptarget tracking with improved kernelized correlation filters

DONG Chao;ZHENG Bing;LI Bin;TIAN Lian-fang;LIU Wei;South China Sea Marine Survey and Technology Center,State Oceanic Administration,Key laboratory of Technology and Application for Safeguarding of Marine Rights and Interests,State Oceanic Administration;South China University of Technology;  
To achieve tracking of marine vessel targets and improve maritime intelligence monitoring levels,this study proposed a target tracking algorithm with improved kernelized correlation filters(KCF).First,per the characteristics of a KCF algorithm,the concept of ship target tracking critical probability was proposed for evaluating whether target tracking was abnormal.A Kalman filter module was added to the algorithm to predict the position of the tracking target at the next moment.A target tracking exception processing module was needed when tracking was abnormal,and an exception handling strategy was adopted.Finally,four sets of typical target tracking scenarios at sea were used to verify the performance of the algorithm through experiments.Under scenarios of largescale shaking of the ship,tracking target occlusion,target out of bounds,and target size change,the result shows the accuracy of our algorithm to be 17.23% higher than that of the original KCF algorithm,and the rate is increased by 7.86%.Thus,our algorithm meets the requirements of ship tracking accuracy,real-time performance,and applicability.
【Fund】: 海洋公益性行业科研专项经费资助项目(No.201505002);; 国家海洋局南海分局海洋科学技术局长基金资助项目(No.180214);; 全球变化与海气相互作用专项资助
【CateGory Index】: TP391.41;TN713;U675.79
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