Izvorni znanstveni članak
https://doi.org/10.24138/jcomss.v14i2.514
A Method of Multi-component Signal Detection Based on Differential Nonlinear Mode Decomposition
Tiantian Yang
orcid.org/0000-0003-1509-8509
; Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
Jie Shao
; Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
Yue Huang
; Nanjing Univ. Aeronaut. Astronaut.), Ministry of Education, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China
Reza Malekian
orcid.org/0000-0002-2763-8085
; Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, 0002, South Africa
Sažetak
In order to detect the multi-component signal from the noise and chaos, a method based on the differential nonlinear mode decomposition (DNMD) is proposed in this paper. This new analysis approach applies the differential to the original signal. Then the nonlinear mode decomposition (NMD) is used to obtain a series of meaningful nonlinear modes, which has the advantage of extracting high frequency components with small amplitudes and learns from the superiority of NMD such as noise robust. Finally, the spectrum analysis is used to the decomposed components. The analysis of simulation signals and the real underwater signal is given to demonstrate the effectiveness of this method. Proposed method can detect multi-component signals of time-varying amplitude without fake frequency under the condition of noise and chaos. Compared with traditional decomposition methods, the peaks of Hilbert marginal spectrum of proposed method are sharper, and R2, R3 are higher.
Ključne riječi
Multi-component signal detection; Differential nonlinear mode decomposition; Chaos; Spectrum analysis
Hrčak ID:
202887
URI
Datum izdavanja:
5.6.2018.
Posjeta: 772 *