EDP Sciences logo
Submit your paper
Search
Menu
All issues Volume 42 / No 3 (June 2024) JNWPU, 42 3 (2024) 417-425 References
Open Access
Issue
JNWPU
Volume 42, Number 3, June 2024
Page(s) 417 - 425
DOI https://doi.org/10.1051/jnwpu/20244230417
Published online 01 October 2024
  1. SUN Tongjing, JIN Jiwei, LIU Tong, et al. Active sonar target classification method based on fisher's dictionary learning[J]. Applied Sciences, 2021, 11(22): 10635 [Article] [CrossRef] [Google Scholar]
  2. WANG Zirui, WU Jing, WANG Haitao, et al. A torpedo target recognition method based on the correlation between echo broadening and apparent angle[J]. Applied Sciences, 2022, 12(23): 12345 [Article] [CrossRef] [Google Scholar]
  3. WU Yushuang, LI Xiukun, WANG Yang. Extraction and classification of acoustic scattering from underwater target based on Wigner-Ville distribution[J]. Applied Acoustics, 2018, 138: 52–59 [Article] [CrossRef] [Google Scholar]
  4. SHI Danhua, HU Binan, HUANG Junxi. State-of-the-art of foreign underwater acoustic countermeasures and their development trends[J]. Ship Science and Technology, 2020, 42(9): 174–180 [Article] (in Chinese) [Google Scholar]
  5. ZHANG Mingyang, LIU Yudong. Development status and trend of acoustic decoy anti-torpedo underwater acoustic countermeasures[J]. Digital Ocean & Underwater Warfare, 2023, 6(1): 111–117 [Article] (in Chinese) [Google Scholar]
  6. 何文翔, 王海涛, 颜彬. 二维尺度目标模拟系统: 中国, CN201710862224.7[P]. 2018-04-06 [Google Scholar]
  7. LI Junhao, YANG Honghui. The underwater acoustic target timbre perception and recognition based on the auditory inspired deep convolutional neural network[J]. Applied Acoustics, 2021, 182: 108210 [Article] [CrossRef] [Google Scholar]
  8. JIN Leilei, LIANG Hong, YANG Changsheng. Sonar image recognition of underwater target based on convolutional neural network[J]. Journal of Northwestern Polytechnical University, 2021, 39(2): 285–291 [Article] (in Chinese) [Google Scholar]
  9. LIU Feng, SHEN Tangsheng, LUO Zailei, et al. Underwater target recognition using convolutional recurrent neural networks with 3-D Mel-spectrogram and data augmentation[J]. Applied Acoustics, 2021, 178107989 [Article] [CrossRef] [Google Scholar]
  10. WANG Zhong, LIU Liwen, WANG Chenyu, et al. Data enhancement of underwater high-speed vehicle echo signals based on improved generative adversarial networks[J]. Electronics, 2022, 11(15): 2310 [Article] [CrossRef] [Google Scholar]
  11. CAO Wenjing. Design and acceleration of deep neural network for few-shot underwater target recognition[D]. Tianjin: Tiangong University, 2021 (in Chinese) [Google Scholar]
  12. TANG Weilin. Highlight model of echoes from sonar targets[J]. Acta Acustica, 1994, 19(2): 92–100 [Article] (in Chinese) [Google Scholar]
  13. ZHAO Anbang, HE Cheng, HUI Juan, et al. Research of sonar echo highlights measurement[C]//OCEANS 2014-TAIPEI, Taipei, 2014: 1–9 [Google Scholar]
  14. LIU Wenyuan, ZHAO Jinhai. Underwater target modeling technology based on modified highlight model[J]. Torpedo Technology, 2010, 18(5): 352–356 [Article] (in Chinese) [Google Scholar]
  15. DENG Kai, XIANG Xiaomei, GU Jie. Multi-highlight model of scaling acoustic decoy[J]. Technical Acoustics, 2011, 30(2): 201–205 [Article] (in Chinese) [Google Scholar]
  16. ZHAO Song, LI Lanrui, ZHANG Xinhua, et al. Simulation of backscatter signal of submarine target based on spatial distribution characteristics of target intensity[C]//2021 OES China Ocean Acoustics, Harbin, 2021: 234–239 [Google Scholar]
  17. DENG Wei. Application of fine echo characteristics of submarine in torpedo homing[D]. Shanghai: Shanghai Jiaotong University, 2014 (in Chinese) [Google Scholar]
  18. LIU Xiaochun, DONG Chunkai. A method of distinguishing submarine and acoustic decoy based on features of target space dimension[J]. Torpedo Technology, 2008, 16(5): 46–50 [Article] (in Chinese) [Google Scholar]
  19. LONG Yang, LIU Li, SHEN Fumin, et al. Zero-shot learning using synthesised unseen visual data with diffusion regularisation[J]. IEEE Trans on Pattern Analysis and Machine Intelligence, 2018, 40(12): 2498–2512 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.