A Nonlinear Method of Characteristic Extraction for Underwater target Recognition

被引:0
|
作者
Li, Nan [1 ,2 ]
Li, Xiu-kun [1 ,3 ]
机构
[1] Harbin Engn Univ, Coll Underwater Acoust Engn, Harbin 150001, Peoples R China
[2] Northeast Dianli Univ, Coll Informat Engn, Chuanying 132012, Jilin, Peoples R China
[3] Harbin Engn Univ, Natl Key Lab Underwater Acoust Technol, Harbin 150001, Peoples R China
关键词
Radiated noise; Period line spectrum; Empirical mode decomposition; Stochastic resonance;
D O I
10.1109/CICN.2014.80
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Underwater target radiated noise signal possesses the features of non-stationary, non-Gaussian and strong background noise. It's difficult to detect characteristics at low signal-noise ratio. Empirical Mode decomposition algorithm is used to handle tranquilization of radiation noises, and then filtered sub-band signal is fed into the improved model of stochastic resonance. By changing internal noise intensity of the system, enhancement of the weak periodic signal is realized under the synergies of system, signal and noise. The simulation results show that the weak signal power spectrum value is improved nearly 25dB when the algorithm is used for detecting characteristics of actual underwater signal.
引用
收藏
页码:324 / 328
页数:5
相关论文
共 50 条
  • [21] A Nonlinear Feature Extraction Method for Phoneme Recognition
    Gauci, O.
    Debono, C. J.
    Micallef, P.
    2008 IEEE MEDITERRANEAN ELECTROTECHNICAL CONFERENCE, VOLS 1 AND 2, 2008, : 790 - 794
  • [22] Scattering Characteristic Extraction Method for Manmade Target Based on Target Null Theory
    Lu, Dongwei
    Pang, Jiazhi Ma Bo
    Guan, Yifu
    Feng, Dejun
    RADIOENGINEERING, 2023, 32 (01) : 91 - 102
  • [23] Multi-scale spectral feature extraction for underwater acoustic target recognition
    Jiang, Junjun
    Shi, Tuo
    Huang, Min
    Xiao, Zhongzhe
    MEASUREMENT, 2020, 166
  • [24] Deep Learning Feature Extraction for Target Recognition and Classification in Underwater Sonar Images
    Zhu, Pingping
    Isaacs, Jason
    Fu, Bo
    Ferrari, Silvia
    2017 IEEE 56TH ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2017,
  • [25] Study on the characteristic extraction method of moving target based on cyclostationary
    Zhang, Jun
    Fu, Qiang
    Chen, Fu-Bin
    Xiao, Huai-Tie
    Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics, 2002, 24 (06):
  • [26] A Method of Fusion Recognition Based on the Characteristic of Target and Incomplete Data
    Li Jun-wu
    Yu Zhi-fu
    PROCEEDINGS OF 2012 IEEE 11TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP) VOLS 1-3, 2012, : 1813 - 1816
  • [27] Fast target recognition and tracking method based on characteristic corner
    State Key Lab. of Precision Measurement Technology and Instruments, College of Precision Instrument and Optoelectronic Engineering, Tianjin University, Tianjin 300072, China
    Guangxue Xuebao, 2007, 2 (360-364): : 360 - 364
  • [28] OPTICAL CHARACTER RECOGNITION USING A NEW METHOD OF CHARACTERISTIC EXTRACTION
    SHONO, Y
    INUZUKA, T
    APPLIED OPTICS, 1972, 11 (05): : 1271 - &
  • [29] A Novel Underwater Acoustic Target Identification Method Based on Spectral Characteristic Extraction via Modified Adaptive Chirp Mode Decomposition
    Li, Zipeng
    Yang, Kunde
    Zhou, Xingyue
    Duan, Shunli
    ENTROPY, 2023, 25 (04)
  • [30] A Novel Underwater Acoustic Target Recognition Method Based on MFCC and RACNN
    Liu, Dali
    Yang, Hongyuan
    Hou, Weimin
    Wang, Baozhu
    SENSORS, 2024, 24 (01)