Time-frequency analysis method and system

Abstract

The invention discloses a time-frequency analysis method and system. The method comprises the following steps of carrying out first signal decomposition on an input signal, carrying out second signaldecomposition on the signals obtained by the first signal decomposition to obtain three signals with the same length, windowing the three signals obtained by the second signal decomposition to obtainthree windowed signals, respectively carrying out symmetrical discrete Fourier transform on the three windowed signals to obtain three frequency domain signals, summing the imaginary parts of the three frequency domain signals respectively, and summing the real parts of the three frequency domain signals respectively, calculating the instantaneous frequency of the signal according to the imaginarypart summation result, and calculating a direct current component, an origin phase and an amplitude of the signal according to the calculated instantaneous frequency and a real part summation result.The method realizes the calculation of the instantaneous frequency, the DC component, the instantaneous amplitude and the instantaneous phase, is suitable for stationary signals and non-stationary signals, and has the advantages of high calculation precision, almost no requirement for signal length, strong DC interference resistance and short calculation time.

Description

technical field [0001] The invention belongs to the technical field of signal analysis, and more specifically relates to a time-frequency analysis method and system. Background technique [0002] Signal is the carrier of information, and people's understanding of everything in the world and communication are based on the understanding of information. Obtaining information from a signal relies on signal analysis. Usually the actual signals are time-varying signals, and scientists often use non-stationary signals to refer to time-varying signals. Time-frequency analysis is widely used in the analysis of non-stationary signals, such as gravitational waves, animal language, brain waves and other signals. With the deepening of human understanding of the world, the requirements for time-frequency analysis methods are getting higher and higher. [0003] There are various time-frequency analysis methods in the prior art. For example, linear time-frequency representation, bilinea...

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Problems solved by technology

[0004] Problem 1 in the existing time-frequency analysis method: There is a large error in the calculation of frequency parameters for non-stationary signals

The theoretical basis of the time-frequency analysis of non-stationary signals is that any non-stationary signal can be regarded as the end-to-end connection of short-term stationary signals. Selecting more samples shakes this theoretical basis, which in turn causes a large gap in the estimation of the frequency parameters of non-stationary signals. error

[0005] There is still problem 2 in the existing time-frequency analysis method: the amplitude and phase change information is lost

Taking the short-time Fourier transform (STFT) as an example, the time-frequency diagram can only approximately reflect the relationship between time and frequency, and loses the amplitude and phase information

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