Skip to the main content

Journal of Communications Software and Systems, Vol. 14 No. 2, 2018.

Original scientific paper

https://doi.org/10.24138/jcomss.v14i2.514

A Method of Multi-component Signal Detection Based on Differential Nonlinear Mode Decomposition

Tiantian Yang orcid id 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 id orcid.org/0000-0002-2763-8085 ; Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, 0002, South Africa

Full text: english pdf 1.488 Kb

page 171-179

downloads: 370

cite

Abstract

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.

Keywords

Multi-component signal detection; Differential nonlinear mode decomposition; Chaos; Spectrum analysis

Hrčak ID:

202887

URI

https://hrcak.srce.hr/202887

Publication date:

5.6.2018.

Visits: 1.059 *