引用本文: | 李余兴,李亚安,陈晓,等.基于VMD和SVM的舰船辐射噪声特征提取及分类识别[J].国防科技大学学报,2019,41(1):89-94.[点击复制] |
LI Yuxing,LI Yaan,CHEN Xiao,et al.Feature extraction and classification of ship radiated noise based on VMD and SVM[J].Journal of National University of Defense Technology,2019,41(1):89-94[点击复制] |
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基于VMD和SVM的舰船辐射噪声特征提取及分类识别 |
李余兴, 李亚安, 陈晓, 蔚婧 |
(西北工业大学 航海学院, 陕西 西安 710072)
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摘要: |
针对复杂海洋背景下舰船声频辐射噪声特征提取困难的问题,提出一种基于变分模态分解、中心频率、复杂度特征和支持向量机的舰船辐射噪声特征提取及分类识别方法。对四类舰船辐射噪声信号使用变分模态方法分解,得到一定数量的固有模态函数。通过比较提取能量最大的固有模态函数中心频率和排列熵作为特征参数,并利用支持向量机方法对四类舰船信号样本进行分类识别。实验结果表明,该方法可以实现对舰船辐射噪声的特征提取,与已有方法对比,该方法具有较高的识别率。 |
关键词: 变分模态分解 复杂度 支持向量机 特征提取 分类识别 |
DOI:10.11887/j.cn.201901013 |
投稿日期:2017-04-16 |
基金项目:国家自然科学基金资助项目(51179157,51409214,11574250) |
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Feature extraction and classification of ship radiated noise based on VMD and SVM |
LI Yuxing, LI Yaan, CHEN Xiao, YU Jing |
(School of Marine Science and Technology, Northwestern Polytechnical University, Xi′an 710072, China)
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Abstract: |
In order to solve the problem that the feature extraction of ship radiated noise in complex ocean environment is difficult, a method for feature extraction and classification of ship radiated noise based on variational mode decomposition, center frequency, complexity and support vector machine was presented. Four kinds of ship radiated noise signals were decomposed into several intrinsic mode functions with variational mode decomposition. In comparison, the center frequency and permutation entropy of intrinsic mode function with the maximum energy were taken as the characteristic parameters. The characteristic parameters acted as the input of support vector machine to distinguish the four kinds of ship. Results show that this method can realize the feature extraction of ship radiated noise, and it has higher recognition rate than the existing methods. |
Keywords: variational mode decomposition complexity support vector machine feature extraction classification and recognition |
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