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引用本文:田西兰,李川,王,孙瑞,刘丽莎. 智能化军用雷达目标识别关键问题探讨[J]. 雷达科学与技术, 2021, 19(5): 534-538.[点击复制]
TIAN Xilan, LI Chuan, WANG Feng, SUN Rui, LIU Lisha. Discussion on Key Problems in Intelligent Military Radar Target Recognition[J]. Radar Science and Technology, 2021, 19(5): 534-538.[点击复制]
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智能化军用雷达目标识别关键问题探讨
田西兰,李川,王,孙瑞,刘丽莎
1.中国电子科技集团公司第三十八研究所,安徽合肥230088;2.孔径阵列与空间探测安徽省重点实验室,安徽合肥230088
摘要:
随着人工智能等前沿技术的迅速发展和战场环境的日趋复杂,智能化军用雷达目标识别的需求愈加迫切。本文结合国内外目标识别的发展趋势和深度学习算法在雷达目标识别中的应用研究,从实装应用的角度出发,探讨了军用雷达智能化目标识别各处理环节的关键问题,分别在层次化目标识别策略设计、目标稳健特征提取与特性自学习以及决策模型设计等方面开展了较为全面、深入的分析,论述了未来应用研究中的重要方向,给智能化目标识别设计提供参考。
关键词:  人工智能  雷达目标识别  特征自学习  层次化识别
DOI:DOI:10.3969/j.issn.1672-2337.2021.05.009
分类号:TN959
基金项目:
Discussion on Key Problems in Intelligent Military Radar Target Recognition
TIAN Xilan, LI Chuan, WANG Feng, SUN Rui, LIU Lisha
1.The 38th Research Institute of China Electronics Technology Group Corporation, Hefei 230088, China;2. Key Laboratory of Aperture Array and Space Application,Hefei 230088,China
Abstract:
With the rapid development of artificial intelligence and the increasingly complex battlefield environment, the demand of intelligent military radar target recognition is becoming more and more urgent. From the view of real application, combined with the development trend of target recognition at home and abroad and the deep learning algorithm in radar target recognition application research, the key problems in each processing step are discussed in this paper. Hierarchical target recognition strategy design, robust target features extraction and feature self-learning, as well as the decision model design are comprehensively and deeply analyzed. The important directions of future application research are discussed, which provides a reference solution.
Key words:  artificial intelligence  radar target recognition  feature self-learning  hierarchical recognition

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