A method for adaptive time-frequency transformation of polynomial phase signal based on genetic optimization

Abstract

The present invention provides a polynomial phase signal adaptive time-frequency transformation method based on genetic optimization, which can complete the time-frequency decomposition of the polynomial phase signal, wherein each signal component obtained by the decomposition is a single frequency point corresponding to only one frequency point at any moment. component, and then use each signal component and the instantaneous frequency value at each moment to directly calculate and generate the signal frequency distribution corresponding to the corresponding moment through the Sinc function that only retains the main lobe response, which overcomes the traditional time-frequency transformation that corresponds to multiple frequencies at one moment. The non-single component of the point has the defect of cross-terms, and finally outputs the time-frequency distribution without any cross-term interference and the time-frequency joint resolution is better; the principle of the invention is simple, the operation is convenient, and it can effectively overcome the cross-term interference of the classic time-frequency analysis method The adverse effect and the loss of time-frequency joint resolution can effectively improve the quality and efficiency of time-frequency analysis of non-stationary polynomial phase signals.

Description

Technical field [0001] The invention belongs to the field of signal processing, and in particular relates to a polynomial phase signal adaptive time-frequency transformation method based on genetic optimization. Background technique [0002] Many natural and artificial signals, such as voice, biomedical signals, waves propagating in dispersive media, mechanical vibrations, animal sounds, music, radar, sonar signals, etc., are typical non-stationary signals, which are characterized by continuous Time is limited, and frequency is time-varying, with non-stationary, non-linear, non-uniform, non-structural, non-deterministic, non-integrable, non-reversible, amorphous, irregular, non-continuous, non-smooth, non-periodic, non- Symmetry and other characteristics. Joint time-frequency analysis (joint time-frequency analysis, referred to as time-frequency analysis) focuses on the time-varying characteristics of real signal components, and expresses a one-dimensional time signal in the for...

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Problems solved by technology

[0018] However, the existing time-frequency analysis methods are still difficult to fully apply to polynomial phase signals whose phase modulation can be expressed as a finite term polynomial series

[0019] The patent "A New Method for Model-Driven Adaptive Time-Frequency Decomposition of Polynomial Phase Signals" proposed a feasible new idea and method for the above-mentioned practical problems, but did not give specific details of various modern optimization algorithms among them. Practical operation and calculation process

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