An Adaptive Time-Frequency Transformation Method of Polynomial Phase Signal Based on Ant Colony Optimization

Abstract

The invention provides a polynomial phase signal self-adaptive time-frequency transform method based on ant colony optimization. The time-frequency decomposition of a polynomial phase signal can be completed, each decomposed signal component is simple component only corresponding to one frequency point at any moment; and then various signal components, and the instantaneous frequency values of various moments are used for directly computing to generate the corresponding signal frequency distribution at corresponding moment by only reserving a Since function of the main lobe response; a defectthat cross-terms are existent in the non-simple component with one moment corresponding to multiple frequency points in the traditional time-frequency transform is overcome; and the time-frequency distribution without any cross-term interference and with optimal time-frequency combined resolution is output finally. The polynomial phase signal self-adaptive time-frequency transform method providedby the invention is simple in principle and convenient for operation, the bad influence by the cross-term interference of a classic cross-term interference and the loss of the time-frequency combinedresolution can be effectively overcome, and the quality and the benefit of a non-stationary polynomial phase signal time-frequency analysis can be effectively improved.

Description

technical field [0001] The invention belongs to the field of signal processing, in particular to an ant colony optimization-based polynomial phase signal adaptive time-frequency transformation method. 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-dime...

AI Technical Summary

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 Model-Driven Polynomial Phase Signal Adaptive Time-Frequency Transformation Method" proposes a feasible new idea and method for the above-mentioned practical problems, but does not specifically give the specific practicality of various modern optimization algorithms. Operation and Calculation Process

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