多模态信息融合舰船目标识别研究进展  被引量:2

A Review of Ship Target Recognition Based on Multi-modal Information Fusion

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作  者:吴文静 王中训[1] 但波 邢子杰 WU Wenjing;WANG Zhongxun;DAN Bo;XING Zijie(School of Physics and Electronic Information,Yantai University,Yantai 264005,China;College of Coast Guard,Naval Aviation University,Yantai 264001,China;Shandong Technology and Business University,Yantai 264026,China)

机构地区:[1]烟台大学物理与电子信息学院,山东烟台264005 [2]海军航空大学岸防兵学院,山东烟台264001 [3]山东工商学院,山东烟台264026

出  处:《探测与控制学报》2024年第2期1-12,共12页Journal of Detection & Control

基  金:国防科技重点实验室基金项目(2021-JCJQ-LB-018)。

摘  要:舰船目标识别的信息源主要来自现代高分辨率成像雷达形成的舰船目标信息,包括高分辨距离像、船舶自动识别系统信息以及合成孔径雷达成像。在对海探测环境相对复杂的情况下,基于单模态信息对海上舰船目标识别的能力有限,而利用多模态信息融合将更有益于实现对海上目标高效的侦察监视和识别。首先,对单模态舰船目标识别方法进行梳理和总结,分析目前不同舰船目标识别方法存在的优势和不足;然后对多模态信息融合舰船目标识别常用数据集进行介绍,并对新方法、新模型进行了深入分析;最后对舰船目标识别未来发展趋势进行展望,为后续基于多模态信息融合的舰船目标识别方法研究提供参考。At present,the information source for ship target recognition mainly comes from ship target information formed by modern high-resolution imaging radar,including high-resolution range profiles,ship automatic recognition system information,and synthetic aperture radar imaging.In the context of relatively complex sea exploration environments,the ability to identify ship targets on the sea based on single mode information is limited,and utilizing multi-modal information fusion will be more beneficial for achieving efficient reconnaissance,monitoring,and identification of sea targets.This article first sorts out and summarizes the methods of single mode ship target recognition,analyzes the advantages and disadvantages of different ship target recognition methods at present,introduces the commonly used datasets of multi-modal information fusion ship target recognition,and conducts in-depth analysis of new methods and models.Finally,it looks forward to the future development trend of ship target recognition.This article can provide reference for future research on ship target recognition methods based on multi-modal information fusion.

关 键 词:高分辨距离像 船舶自动识别系统 合成孔径雷达 多模态信息融合 舰船目标识别 

分 类 号:TP183[自动化与计算机技术—控制理论与控制工程]

 

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