基于模态函数特征谱的海洋小目标检测
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。...
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| Published in | 电子技术应用 Vol. 43; no. 5; pp. 114 - 118 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
武汉大学地球空间信息技术协同创新中心,湖北武汉430079%武汉大学电子信息学院,湖北武汉,430072
2017
武汉大学电子信息学院,湖北武汉430072 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0258-7998 |
| DOI | 10.16157/j.issn.0258-7998.2017.05.028 |
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| Abstract | 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。 |
|---|---|
| AbstractList | 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。 TN958.95; 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. |
| Abstract_FL | 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 appropriate 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. |
| Author | 陈泽宗 杨干 赵晨 贺超 |
| AuthorAffiliation | 武汉大学电子信息学院,湖北武汉430072 武汉大学地球空间信息技术协同创新中心,湖北武汉430079 |
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| Author_FL | Yang Gan Zhao Chen He Chao Chen Zezong |
| Author_FL_xml | – sequence: 1 fullname: Chen Zezong – sequence: 2 fullname: Yang Gan – sequence: 3 fullname: Zhao Chen – sequence: 4 fullname: He Chao |
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| DocumentTitleAlternate | Small target detection in sea clutter based on characteristic spectrum of intrinsic mode functions |
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| Keywords | 特征谱 海杂波 microwave Doppler radar target detection empirical mode decomposition characteristic spectrum 微波多普勒雷达 目标检测 经验模态分解 sea clutter |
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| Notes | Chen Zezong1,2, Yang Gan1, Zhao Chen1, He Chao1 （1.School of Electronic Information, Wuhan University, Wuhan 430072, China ; 2.Collaborative Innovation Center for Geospatial Technology, Wuhan University, Wuhan 430079, China） microwave Doppler radar ; target detection ; empirical mode decomposition ; characteristic spectrum ; sea clutter 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 dist |
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| PublicationTitle | 电子技术应用 |
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| Publisher | 武汉大学地球空间信息技术协同创新中心,湖北武汉430079%武汉大学电子信息学院,湖北武汉,430072 武汉大学电子信息学院,湖北武汉430072 |
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| Snippet | 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... TN958.95; 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... |
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| SubjectTerms | 微波多普勒雷达 海杂波 特征谱 目标检测 经验模态分解 |
| Title | 基于模态函数特征谱的海洋小目标检测 |
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