Fundamental Frequency Detection of Underwater Acoustic Target Using DEMON Spectrum and CNN Network
文献类型：会议论文
| 作者 | Lu JM(卢佳敏); Song SM(宋三明) ; Hu ZQ(胡志强); Li S(李硕)
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| 出版日期 | 2020 |
| 会议日期 | November 27-28, 2020 |
| 会议地点 | Harbin, China |
| 关键词 | Fundamental frequency detection CNN DEMON comb filter hydrophone array signal |
| 页码 | 778-784 |
| 英文摘要 | The fundamental frequency, or F0, is directly determined by the vibration frequency of sound source. Therefore, by detecting and tracking F0, it is possible to estimate the attributes and motion state of an underwater maneuvering object, including the rotation speed of the propeller, the shaft number and so on. Unfortunately, coupled with mechanical noise and continuous noise, and further polluted by the marine ambient noise, some spectral lines that correspond to the the fundamental frequency and its harmonics would be distorted, like amplitude attenuation or position shift, which severely discounts the detection precision of the state-of-art methods. To improve the precision and stability of F0 detection, especially in low SNR situation, we propose to estimate the state of sound source by learning the hydrophone array signal with a deep neural network. Specifically, in the preprocessing stage, the DEMON spectrum is extracted from noise signal for each hydrophone channel, and it is subsequently cleaned by the wavelet denoising. Then, we use a comb filter to compensate the spectral line distortion effects. Finally, the purified frequency spectrum features are fed into a CNN network to determine F0 by classification. Simulation experiments show that the data-driven deep learning method outperforms traditional model-based algorithms in the case of low-SNR noise signals. |
| 产权排序 | 1 |
| 会议录 | 2020 3rd International Conference on Unmanned Systems (ICUS)
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| 会议录出版者 | IEEE |
| 会议录出版地 | New York |
| 语种 | 英语 |
| ISBN号 | 978-1-7281-8025-0 |
| WOS记录号 | WOS:000648775600136 |
| 源URL | [http://ir.sia.cn/handle/173321/28001]  |
| 专题 | 海洋机器人卓越创新中心 所领导 |
| 通讯作者 | Lu JM(卢佳敏) |
| 作者单位 | State Key Laboratory of Robotics, Shenyang Institute of Automation, CAS, Shenyang, China |
| 推荐引用方式 GB/T 7714 | Lu JM,Song SM,Hu ZQ,et al. Fundamental Frequency Detection of Underwater Acoustic Target Using DEMON Spectrum and CNN Network[C]. 见:. Harbin, China. November 27-28, 2020. |
入库方式： OAI收割
来源：沈阳自动化研究所
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