TIME-FREQUENCY-BASED METHODS: APPLICATIONS TO SIGNAL ANALYSIS

Resumen

In communication systems it is of major importance the study of signals not only in time but also in the frequency domain. This is needed to characterize central frequency, bandwidth, channel effects or noise.

This is useful to set properly transmitters and receivers. This paper is concerned with the time-frequency methods applied to signal analysis in time and frequency domains simultaneously. Two main approaches are defined, the instantaneous frequency (IF) and the Time-Frequency Representations (TFR) of signals.

Unlike the Fourier transform, IF and TFR both allow to describe the evolution of the frequency content of a signal. Thus, non-stationary signals are better analyzed by means of these two approaches than by the use of the Fourier transform. IF is a useful and low complexity technique to analyze monocomponent signals, while TFRs described by the Short-Time Fourier Transform (STFT) and the Time-Frequency

Distributions (TFDs) are commonly applied to analyze multicomponent signals. This paper is oriented to describe the main TFR and IF techniques, as well as to discuss the main differences regarding the Fourier transform. The theory behind this techniques is illustrated by some simulations.