| 摘要: |
| 在海杂波背景下，慢速小目标的检测一直是雷达信号处理中的难点之一。这类目标的时频域特征往往与海杂波的特征高度重叠，使得传统的检测方法难以有效区分目标和杂波。为了应对这一挑战，本文提出了一种基于多种模态分解重构的办法，通过变分模态分解与分数阶傅立叶变换对海杂波背景下的目标信号进行分解，并用能量熵和奇异值分解方法重构目标信号。实测数据验证了该方法在海杂波抑制方面的显著效果，表明其可以显著提升雷达在复杂海况中的小目标检测性能，为海杂波环境下的目标检测提供了新思路和技术手段。 |
| 关键词: 海杂波 慢小目标检测 变分模态分解 分数阶傅里叶变换 能量熵 奇异值分解 |
| DOI： |
| 分类号:TN951 |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| The Method for Detecting Slow Small Targets on the Sea Surface Based on Multimodal Decomposition and Reconstruction |
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| Abstract: |
| Slow and small targets in sea clutter are difficult to detect due to the overlap of their time-frequency characteristics with those of the sea clutter. This paper proposes a method based on multimodal decomposition and reconstruction, which decomposes the target signal in sea clutter using variational mode decomposition and fractional Fourier transform, and reconstructs the target signal using energy entropy and singular value decomposition. Experimental data show that this method achieves excellent sea clutter suppression. |
| Key words: sea clutter slow and small target detection variational mode decomposition fractional fourier transform energy entropy singular value decomposition |