吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (2): 653-657.doi: 10.13229/j.cnki.jdxbgxb201502047

• Orignal Article • Previous Articles     Next Articles

New frequency estimation method for harmonic signal submerged in complex noise background

SUN Xiao-dong,QUAN Ai-juan, LI Yong   

  1. College of Communication Engineering, Jilin University,Changchun 130022,China
  • Received:2013-06-25 Online:2015-04-01 Published:2015-04-01

RICH HTML

0   

PDF (PC)

603

Abstract: A new frequency estimation method for harmonic signals embedded in strong chaotic interference is proposed. This method is based on the frequency doubling, wavelet packet theory and cross spectrum theory, and it is composed of three steps. First, using the cycle characteristic of harmonic, the sampling data are equidistantly taken value of the harmonic signals and then construct a new data sequence. The doubling harmonic is deviated from the chaotic centre frequency. Second, the wavelet packet decomposition algorithm is applied to analyze the energy distribution characteristics of the harmonic signals and chaotic signals. Finally, according to the results of second step, the components, on which the harmonic signal energy concentrates, are extracted, then, the cross spectrum method is applied to estimate the frequencies of the harmonic signals. Simulation results demonstrate the effectiveness of the proposed method.

Key words: information processing technology, frequency estimation , chaos signal, frequency doubling, wavelet packet theory , cross spectrum

CLC Number: 

  • TN911.71
[1] 吕金虎,陆君安,陈士华.混沌时间序列分析及其应用[M].武汉:武汉大学出版社,2002:1-10.
[2] Stark J,Arumugaw B.Extracting slowly varying signal from a chaotic background[J].International Journal of Bifurcation and Chaos,1992,2(2):413-419.
[3] Haykin S, Li X B.Detection of signals in chaos[J].Proceedings of IEEE, 1995,83:94.
[4] He Di.Signal estimation in clutter using SVM-based chaos synchronization[C]∥Global Telecommunications Conference, Honolulu:IEEE,2009:1-6.
[5] Manjunath G, Sivaji Ganesh S, Anand G V. Denoising signals corrputed by chaotic noise[J].Communications in Nonlinear Science and Numerical Simulation,2010, 15(12):3988-3997.
[6] Broomhead D S,Huke J P, Potts M A S.Cancelling deterministic noise by constructingnonlinear inverses to linear filters[J].Physica D,1996,89:439-458.
[7] 李鸿光,孟光.基于经验模式分解的混沌干扰下谐波信号的提取方法[J].物理学报,2004,53(7) : 2069-2073.
Li Hong-guang,Meng Guang. Harmoic signal extraction from chaotic interference based on empirical mode decomposition[J]. Acta Physica Sinica,2004,53(7) : 2069-2073.
[8] 陆振波,蔡志明.基于Volterra滤波器的混沌背景弱信号检测[J].系统仿真学报,2008, 20(7):1778-1780.
Lu Zhen-bo,Cai Zhi-ming.Weak signal detection in chaos based on Volterra filter[J].Journal of System Simulation,2008, 20(7):1778-1780.
[9] Xiang X Q, Shi B C. Weak signal detection based on the information fusion and chaotic oscillator[J]. Chaos, 2010, 20(1):013104.
[1] YING Huan,LIU Song-hua,TANG Bo-wen,HAN Li-fang,ZHOU Liang. Efficient deterministic replay technique based on adaptive release strategy [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1917-1924.
[2] LIU Zhong-min,WANG Yang,LI Zhan-ming,HU Wen-jin. Image segmentation algorithm based on SLIC and fast nearest neighbor region merging [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1931-1937.
[3] SHAN Ze-biao,LIU Xiao-song,SHI Hong-wei,WANG Chun-yang,SHI Yao-wu. DOA tracking algorithm using dynamic compressed sensing [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1938-1944.
[4] YAO Hai-yang, WANG Hai-yan, ZHANG Zhi-chen, SHEN Xiao-hong. Reverse-joint signal detection model with double Duffing oscillator [J]. 吉林大学学报(工学版), 2018, 48(4): 1282-1290.
[5] QUAN Wei, HAO Xiao-ming, SUN Ya-dong, BAI Bao-hua, WANG Yu-ting. Development of individual objective lens for head-mounted projective display based on optical system of actual human eye [J]. 吉林大学学报(工学版), 2018, 48(4): 1291-1297.
[6] CHEN Mian-shu, SU Yue, SANG Ai-jun, LI Pei-peng. Image classification methods based on space vector model [J]. 吉林大学学报(工学版), 2018, 48(3): 943-951.
[7] CHEN Tao, CUI Yue-han, GUO Li-min. Improved algorithm of multiple signal classification for single snapshot [J]. 吉林大学学报(工学版), 2018, 48(3): 952-956.
[8] MENG Guang-wei, LI Rong-jia, WANG Xin, ZHOU Li-ming, GU Shuai. Analysis of intensity factors of interface crack in piezoelectric bimaterials [J]. 吉林大学学报(工学版), 2018, 48(2): 500-506.
[9] LIN Jin-hua, WANG Yan-jie, SUN Hong-hai. Improved feature-adaptive subdivision for Catmull-Clark surface model [J]. 吉林大学学报(工学版), 2018, 48(2): 625-632.
[10] WANG Ke, LIU Fu, KANG Bing, HUO Tong-tong, ZHOU Qiu-zhan. Bionic hypocenter localization method inspired by sand scorpion in locating preys [J]. 吉林大学学报(工学版), 2018, 48(2): 633-639.
[11] YU Hua-nan, DU Yao, GUO Shu-xu. High-precision synchronous phasor measurement based on compressed sensing [J]. 吉林大学学报(工学版), 2018, 48(1): 312-318.
[12] WANG Fang-shi, WANG Jian, LI Bing, WANG Bo. Deep attribute learning based traffic sign detection [J]. 吉林大学学报(工学版), 2018, 48(1): 319-329.
[13] LIU Dong-liang, WANG Qiu-shuang. Instantaneous velocity extraction method on NGSLM data [J]. 吉林大学学报(工学版), 2018, 48(1): 330-335.
[14] TANG Kun, SHI Rong-hua. Detection of wireless sensor network failure area based on butterfly effect signal [J]. 吉林大学学报(工学版), 2017, 47(6): 1939-1948.
[15] SHAN Ze-biao, LIU Xiao-song, WANG Chun-yang, SHI Yi-ran, SHI Yao-wu. Joint estimation of DOA and Doppler frequency for coherence and/or same-direction signals [J]. 吉林大学学报(工学版), 2017, 47(6): 1949-1956.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd