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2017 | 24 | Special Issue S3 |
Tytuł artykułu

Identification algorithm of uncertain sonar signals in complex marine environment

Autorzy
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The current identification algorithm using sonar signal parameters of bandwidth, frequency, duration and pulse waveform which are easy to detect and imitation, to identify the identity of sonar signal, resulting in part of the sonar signal identity is not easy to distinguish. Therefore, an algorithm based on signal feature extraction and digital watermarking is proposed to recognize the uncertain sonar signals. The algorithm embeds the digital watermark into the detection signal from the uncertain sonar. The identity of the signal is recognized by detecting whether the received signal contains watermarks. Experimental results showed that the proposed algorithm can effectively improve the recognition performance of sonar signal source
Słowa kluczowe
EN
Wydawca
-
Rocznik
Tom
24
Opis fizyczny
p.235-242,fig.,ref.
Twórcy
autor
  • School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
Bibliografia
  • 1. Ferguson B G, Lo K W. Passive and active sonar signal processing methods for port infrastructure protection and harbor security. Journal of the Acoustical Society of America, 2016, 140(4):3350-3350.
  • 2. Wei C, Wwl A, Ketten D R, et al. Biosonar signal propagation in the harbor porpoise’s (Phocoena phocoena) head: The role of various structures in the formation of the vertical beam.. Journal of the Acoustical Society of America, 2017, 141(6):4179.
  • 3. Au W W, Copeland A, Martin S W, et al. Comparing the biosonar signals of free swimming dolphins with those of a stationary dolphin in a net pen. Journal of the Acoustical Society of America, 2015, 137(4):2335-2335.
  • 4. Parks J K. Development of a Multichannel Optical Correlation Detector for Sonar Signals. Journal of Aircraft, 2015, 3(3):278-284.
  • 5. Au W W L, Martin S W, Moore P W, et al. Dynamics of biosonar signals in free-swimming and stationary dolphins: The role of source levels on the characteristics of the signals. Journal of the Acoustical Society of America, 2016, 139(3):1381-1389.
  • 6. De Maio A, Orlando D, Hao C, et al. Adaptive Detection of Point-Like Targets in Spectrally Symmetric Interference. IEEE Transactions on Signal Processing, 2016, 64(12):3207-3220.
  • 7. Scandella B P, Pillsbury L, Weber T, et al. Ephemerality of discrete methane vents in lake sediments. Geophysical Research Letters, 2016, 43(9):n/a-n/a.
  • 8. Wei C, Wwl A, Ketten D R, et al. Biosonar signal propagation in the harbor porpoise’s (Phocoena phocoena) head: The role of various structures in the formation of the vertical beam.. Journal of the Acoustical Society of America, 2017, 141(6):4179.
  • 9. Au W W, Copeland A, Martin S W, et al. Comparing the biosonar signals of free swimming dolphins with those of a stationary dolphin in a net pen. Journal of the Acoustical Society of America, 2015, 137(4):2335-2335.
  • 10. LIANG Wei-xin,FENG Yong-xin,QIAN Bo,et al.An Optimization Recognition Algorithm of AmplitudeFrequency Modulation Signals. Computer Simulation, 2016,33(8):415-420.
  • 11. Gao, W. and W. Wang, The fifth geometric-arithmetic index of bridge graph and carbon nanocones. Journal of Difference Equations and Applications, 2017. 23(1-2SI): p. 100-109.
  • 12. Gao, W., et al., Distance learning techniques for ontology similarity measuring and ontology mapping. Cluster Computing-The Journal of Networks Software Tools and Applications, 2017. 20(2SI): p. 959-968.
  • 13. De’nan F, Nazri F M, Hashim N S. Finite Element Analysis on Lateral Torsional Buckling Behaviour Oi I-Beam with Web Opening. Engineering Heritage Journal, 2017, 1(2):19–22.
  • 14. Sarkar M I, Islam M N, Jahan A, Islam A, Biswas J C. Rice straw as a source of potassium for wetland rice cultivation. Geology, Ecology, and Landscapes, 2017, 1(3): 184-189.
  • 15. Foroozanfar M. Environmental control in petroleum operations. Journal CleanWAS, 2017, 1(2): 18-22.
  • 16. Wang J, Xu H. The Crust and Uppermost Mantle S-Wave Velocity Structure Beneath Japan Islands Revealed by Joint Analysis of P - And SWave Receiver Functions. Malaysian Journal Geosciences, 2017, 1(2): 20-23.
  • 17. Tahir S, Siong K Y, Musta B, Asis J. Facies and Sandstone Characteristics of The Kudat Formation, Sabah, Malaysia. Geological Behavior, 2017, 1(2):20–25.
  • 18. Shamsudin S B, Majid A A. Association of blood lead levels and working memory ability of primary school children surrounding ex-copper mining area in Ranau, Sabah (Malaysia). Acta Scientifica Malaysia, 2017, 1(1): 01-03.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.agro-616aee65-5ea2-4d6b-b132-55b4ec029257
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