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A New Parametric Time-frequency Analysis Method for Instantaneous Frequency Estimation of Polynomial Phase Signal
FANG Yang;PENG Zhi-ke;MENG Guang;YANG Yang
2012, 32 (3):
7-11.
DOI: 10.3969/j.issn.1006-1355.2012.03.002
Nonlinear chirplet transform, a new parametric method for time-frequency analysis was proposed by replacing the linear chirp kernel by a nonlinear polynomial kernel. By choosing the proper kernel characteristic parameters, the nonlinear chirplet transform can render a time frequency distribution of excellent concentration for signals whose instantaneous frequency trajectory is an arbitrary function of time. In this paper, the polynomial chirplet transform was applied to estimate the polynomial phase signals with arbitrary order. As the performance of the nonlinear chirplet transform highly depends on the kernel characteristic parameters, an algorithm to evaluate these parameters was developed in order to estimate the instantaneous frequency and the phase parameters of the polynomial phase signal. The effectiveness of the algorithm was validated by analyzing the signals from numerical simulation.
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