Kalman filter-based signal real-time time-frequency spectrometer

Abstract

The invention discloses a kalman filter-based signal real-time time-frequency spectrometer, which comprises a sensor, an A / D data conversion card, a processor, a control panel, a memory and a display; wherein the processor comprises a pretreatment module, a forecast module, a correction module and a smoothing module which are connected orderly. The kalman filter-based signal real-time time-frequency spectrometer is characterized in that a command is input by the control panel; a non-stationary time-varying signal acquired by the processor is sampled and converted by the A / D data conversion card; then the pretreatment module, the forecast module, the correction module and the smoothing module perform forecasting, correction and smoothing treatments on the parameters of signal sampling points orderly; and after the treated parameter is substituted into a time-frequency spectral function, a high-resolution time-frequency spectrum can be obtained, and finally is shown on the display. The time-frequency spectrometer of the invention can carry out real-time, dynamic and continuous treatment on the signals, and can obtain the time-frequency spectrum which has high resolution and no cross-term interference, thereby bringing great convenience to the subsequent signal processing.

Description

technical field [0001] The invention relates to an intelligent dynamic measurement and control system, in particular to a signal real-time time-frequency spectrum generation system based on a Kalman filter. Background technique [0002] Time-frequency analysis is to describe the energy density or intensity of a signal at different times and frequencies by designing a joint function of time and frequency. This joint function of time and frequency is simply called the time-frequency distribution. Using the time-frequency distribution to analyze the signal, the instantaneous frequency and its amplitude at each moment can be given, and time-frequency filtering and time-varying signal research can be carried out. As a powerful tool for analyzing time-varying non-stationary signals, time-frequency analysis has become a hot spot in modern signal processing research. As a new signal processing method, time-frequency analysis has received more and more attention in recent years. It...

AI Technical Summary

Problems solved by technology

In order to obtain a higher frequency resolution, a larger window length needs to be selected, but this will affect the resolution in the time domain. Therefore, the short-time Fourier transform cannot satisfy the time domain and frequency domain resolution at the same time.

When the Wigner-Ville distribution contains only a single time-frequency component, high resolution can be obtained in both the time domain and the frequency domain, but when analyzing multi-frequency component signals, since the signal is a quadratic transformation, it cannot cross term interference

Although the wavelet scale analysis can improve the above interference to a certain extent, the time-frequency resolution of the wavelet scale analysis method will be limited by the uncertainty principle. good resolution

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