Multicomponent Signal Analysis Based on Polynomial Chirplet Transform
Chirplet transform (CT) is effective in characterization of instantaneous frequency (IF) for monocomponent linear-frequency-modulated signal. However, the CT is not suitable to analyze multicomponent signal with nonlinear-frequency-modulated component. In this paper, a time-frequency fusion techniqu...
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| Published in | IEEE transactions on industrial electronics (1982) Vol. 60; no. 9; pp. 3948 - 3956 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.09.2013
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Abstract | Chirplet transform (CT) is effective in characterization of instantaneous frequency (IF) for monocomponent linear-frequency-modulated signal. However, the CT is not suitable to analyze multicomponent signal with nonlinear-frequency-modulated component. In this paper, a time-frequency fusion technique based on polynomial CT (PCT) (TFPCT) is proposed to characterize the time-frequency structure of such signals. The TFPCT relies on the fact that the PCT is able to concentrate the energy closely along the IF of the monocomponent signal in time-frequency distribution (TFD). For multicomponent signal, the TFPCT first estimates the proper coefficients with respect to individual component and, second, produces a series of the TFD using the PCT. Each TFD has better energy concentration along the IF of one component. Then, in order to reduce the interference of unwanted component and preserve the component of interest, each TFD is filtered and grouped as an image. At last, the TFPCT combines these TFDs to be an eventual fused TFD, which has the energy concentrating closely along the IF of all components. Comparison with several conventional TFD methods on both numerical multicomponent signal and bat echolocation signal validates the potential and the effectiveness of the proposed method. |
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| AbstractList | Chirplet transform (CT) is effective in characterization of instantaneous frequency (IF) for monocomponent linear-frequency-modulated signal. However, the CT is not suitable to analyze multicomponent signal with nonlinear-frequency-modulated component. In this paper, a time-frequency fusion technique based on polynomial CT (PCT) (TFPCT) is proposed to characterize the time-frequency structure of such signals. The TFPCT relies on the fact that the PCT is able to concentrate the energy closely along the IF of the monocomponent signal in time-frequency distribution (TFD). For multicomponent signal, the TFPCT first estimates the proper coefficients with respect to individual component and, second, produces a series of the TFD using the PCT. Each TFD has better energy concentration along the IF of one component. Then, in order to reduce the interference of unwanted component and preserve the component of interest, each TFD is filtered and grouped as an image. At last, the TFPCT combines these TFDs to be an eventual fused TFD, which has the energy concentrating closely along the IF of all components. Comparison with several conventional TFD methods on both numerical multicomponent signal and bat echolocation signal validates the potential and the effectiveness of the proposed method. |
| Author | Yang Yang Guang Meng Wenming Zhang Zhike Peng |
| Author_xml | – sequence: 1 givenname: Yang surname: Yang fullname: Yang, Yang – sequence: 2 givenname: Wenming surname: Zhang fullname: Zhang, Wenming – sequence: 3 givenname: Zhike surname: Peng fullname: Peng, Zhike – sequence: 4 givenname: Guang surname: Meng fullname: Meng, Guang |
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| References | ref13 boashash (ref17) 2003 ref12 ref15 ref14 ref11 ref10 ville (ref1) 1958 ref2 ref19 jeffreys (ref18) 1988 angrisani (ref16) 2004 barkat (ref23) 2004; 13 ref26 baraniuk (ref28) 2009 ref25 ref20 ref22 ref21 ref27 haralick (ref24) 1993; i ref8 ref7 ref9 ref4 ref3 ref6 ref5 |
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| SubjectTerms | Approximation methods Chirp Energy concentration Energy distribution Estimates Intermediate frequency Kernel Mathematical models polynomial chirplet transform (CT) (PCT) Polynomials Preserves Signal analysis Strips Time frequency analysis time-frequency representation (TFR) fusion Transforms |
| Title | Multicomponent Signal Analysis Based on Polynomial Chirplet Transform |
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