Signal spectrum zooming method based on linear frequency modulation z transform

Abstract

The invention provides a signal spectrum zooming method based on linear frequency modulation z transform. A symmetrical linear system h(n) is obtained by changing the expression form of a Bluestein equation and carrying out zero filling and periodic extending on the linear system h(n); the method for calculating the Fourier transform of an L point linear system sequence h(n) through a stored L / 2+1 point linear system sequence is put forward; the result q(n) of the circular convolution is horizontally moved leftwards by N0 units, the front M values obtained after horizontal movement are multiplied with k (k=0,1,..., M-1), and then the signal partial spectrum with the improved frequency resolution can be obtained. By means of the scheme, the storage data size of the linear system sequence and the Fourier transform of the linear system sequence can be reduced, the storage space is saved, the Fourier transform of an L point linear system can be calculated through the stored L / 2+1 point linear system data, the calculated quantity of an FFT is reduced, and the calculating efficiency is improved.

Description

technical field [0001] The invention belongs to the technical field of signal spectrum refinement, and in particular relates to a signal spectrum refinement method based on chirp-z transform. Background technique [0002] In the field of spectrum analysis, a fast Fourier transform (FFT) is usually used to perform spectrum analysis on digital signals. However, FFT can only obtain the spectral value of the signal sampling point, and cannot obtain the spectral information between the sampling points, that is, when the peak value of the actual spectrum falls between the sampling point spectra, the FFT cannot obtain the real frequency, amplitude and frequency of the peak value. The phase has a certain influence on the spectrum analysis. In addition, what FFT obtains is the spectrogram in the entire band. Sometimes we only care about the spectrogram of a certain band. At this time, we need to refine the spectrum of the signal. [0003] Spectrum refinement analysis method is to p...

AI Technical Summary

Problems solved by technology

But there are following disadvantages in the prior art: 1, the prior art needs to store the L-point linear system sequence h(n) and its Fourier transform, which takes up more storage resources; 2, the prior art directly uses FFT Calculate the Fourier transform of the L-point linear system h(n). Generally, the data volume N of the signal is large, which makes L also large, resulting in a large amount of FFT calculation at the L-point and low efficiency.

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