An overview of marine moving target detection via high-resolution sparse representation

Xiaohan Yu, Xiaolong Chen, Wenchao Hu, J. Guan
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引用次数: 2

Abstract

Robust and effective detection of marine moving targets in the sea clutter is one of the fundamental and difficult problems in both military and civil fields. There are both advantages and limitations of classical radar detection methods. Sparsity has been proved as a promising tool to solve inverse problems for a high-resolution solution which mathematically may be nonunique. The main purpose of this paper is to provide ideas for marine moving target detection from the view of sparse representation, which utilizes the merits of compressed sensing (CS). First, a brief introduction of sparse representation is given. Then the research status of sparse representation for marine moving target detection is described, the morphological component analysis (MCA) based detection method is introduced, and the feasibility of sparse time-frequency representation used for radar target detection is analyzed. Moreover, we give an example of sparse representation-based marine target detection using real data, which indicates the effectiveness of the detection method. Finally, the future research direction of the detection method is presented.
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基于高分辨率稀疏表示的海洋运动目标检测综述
海杂波中海上运动目标的鲁棒有效检测是军事和民用领域的基础和难点问题之一。传统的雷达探测方法既有优点,也有局限性。稀疏性已被证明是解决数学上可能是非唯一的高分辨率解的反问题的一个很有前途的工具。本文的主要目的是利用压缩感知(CS)的优点,从稀疏表示的角度为海洋运动目标检测提供思路。首先,简要介绍了稀疏表示。然后阐述了稀疏表示用于海洋运动目标检测的研究现状,介绍了基于形态分量分析(MCA)的检测方法,分析了稀疏时频表示用于雷达目标检测的可行性。最后给出了基于稀疏表示的海洋目标检测实例,验证了该方法的有效性。最后,提出了该检测方法未来的研究方向。
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