中文摘要：

经验模态分解算法在海杂波抑制和目标检测方面具有应用潜力,但如何实现模态函数自动筛选和判别是算法的关键问题。通过分析模态函数谐波模型,提取其信号特征谱,选取检测量实现目标自动检测。首先,对雷达回波进行复数经验模态分解;然后对得到的各个内模分量提取特征谱,并根据特征谱分布情况得到散布特征;最后基于散布特征在各个内模函数间的分布差异实现目标检测。实测微波多普勒雷达数据处理结果表明,目标检测结果和实际情况一致,且在一定的虚警率约束下检测概率较传统检测算法有一定提高,为雷达海洋目标检测提供了新方案。

英文摘要：

Empirical mode decomposition algorithm has potential applications in sea clutter suppression and target detection, but how to realize automatic selection and discrimination of modal functions is the key problem of this algorithm. In this paper, by analyzing the harmonic model of modal functions, characteristic spectrums are extracted, and target is detected adaptively after selecting appro- priate features. Firstly, the echoes of radar are preprocessed by complex EMD. Secondly, characteristic spectrum is extracted from each intrinsic mode function, and then distribution characteristics are obtained. Finally, target detection is realized adaptively based on the difference of distribution characteristics in all mode functions between target and sea clutter. Processing of the measured data from microwave Doppler radar shows that the detection results are consistent with the fact, and detection probability is higher than the traditional detection algorithms under a certain false alarm rate. It provides a new guidance for marine radars to detect small targets.