Polynomial phase signal adaptive time frequency transformation method based on genetic optimization

Abstract

The invention provides a polynomial phase signal adaptive time frequency transformation method based on genetic optimization. Time frequency decomposition of polynomial phase signals can be finished,every signal component obtained by decomposition only corresponds to a single component of a frequency point at any time, then values are obtained by the various signal components and instantaneous frequency at any time, signal frequency distribution corresponding to the corresponding time is directly calculated and generated by only retaining a main lobe responded Sinc function, the shortcoming that cross terms exist due to the fact that one time corresponds to non-single components of a plurality of frequency points in the traditional time frequency transformation is overcome, and thus, timefrequency distribution which does not have any cross term interference and has excellent time frequency combined resolution is output finally. The polynomial phase signal adaptive time frequency transformation method based on genetic optimization is simple in principle and convenient to operate; adverse impact of cross term interference of a classic time frequency analysis method and loss of timefrequency combined resolution can be overcome effectively, and the quality and benefit of non-stable polynomial phase signal time frequency analysis can be improved effectively.

Description

technical field [0001] The invention belongs to the field of signal processing, in particular to a polynomial phase signal adaptive time-frequency transformation method based on genetic optimization. Background technique [0002] Many natural and artificial signals, such as speech, 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 the frequency is time-varying, non-stationary, nonlinear, non-uniform, non-structural, non-deterministic, non-integrable, non-reversible, amorphous, irregular, non-continuous, non-smooth, non-periodic, non-smooth symmetrical features. 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 form of a two-dimen...

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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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