Self-adaption instantaneous frequency measuring method with noise suppression performance

Abstract

The invention relates to a self-adaption instantaneous frequency measuring method with noise suppression performance. The self-adaption instantaneous frequency measuring method is characterized by comprising the following steps: (1) decomposing signals needing to be measured by adopting an experience correcting mode, and processing the signals to obtain a plurality of signal components; (2) calculating the instantaneous frequency and the instantaneous amplitude of each signal component by utilizing Teager energy operators; and (3) constructing a time-frequency-energy spectrum of original signals to obtain the instantaneous frequency information of the original signals. According to the method, the noise interference resisting capability is improved simultaneously when the self-adaption signal processing capability decomposed by the preexisting experience mode is reserved, and the mode aliasing phenomenon possibly generated by the preexisting method is avoided.

Description

technical field [0001] The invention relates to the technical field of radio frequency measurement, in particular to an instantaneous frequency measurement method with noise suppression capability, nonlinear and non-stationary signal analysis capability and self-adaptive processing capability. Background technique [0002] Instantaneous frequency measurement technology has a wide range of applications in the fields of communication and radar, and is particularly valuable in the military field. The classic frequency analysis method - Fourier transform is a kind of global analysis method, which cannot obtain the local frequency information of the signal. In order to obtain the information of the instantaneous frequency of the signal, time-frequency analysis tools including short-time Fourier transform, Wigner-Willi distribution and wavelet transform have been proposed one after another. However, the analysis method based on Fourier theory cannot break through the limitation o...

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Problems solved by technology

However, the empirical mode decomposition, the core technology of this method, has certain defects. It has poor resolution for subcomponents with relatively close frequencies (frequency ratio less than 2), and when it is disturbed by noise components, the decomposition method will cause mode aliasing and cause errors. result

In order to improve the frequency measurement accuracy of the Hilbert-Huang variation, an improved method using down-conversion preprocessing and adaptive filter bank as a pre-operation is proposed, but this improved method sacrifices the adaptive characteristics of the original method, and at the same time In the presence of noise interference, it does not have the ability to handle high robustness

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