Abstract :
The Fourier transform has been widely used in radar signal and image processing. When the radar signals exhibit time- or frequency-varying behavior, an analysis that can represent the intensity or energy distribution of signals in the joint time-frequency (JTF) domain is most desirable. In this article, we showed that JTF analysis is a useful tool for improving radar signal and image processing for time- and frequency-varying cases. We applied JTF analysis to radar backscattering and feature extraction; we also examined its application to radar imaging of moving targets. Most methods of JTF analysis are non-parametric. However, parametric or model-based methods of time-frequency analysis, such as adaptive Gaussian and chirplets, are more suitable for radar signals and images
Keywords :
Fourier transforms; backscatter; electromagnetic wave scattering; feature extraction; radar imaging; radar signal processing; signal representation; time-frequency analysis; Fourier transform; adaptive Gaussian method; chirplets; energy distribution; feature extraction; frequency-varying behavior; intensity distribution; joint time-frequency analysis; model-based methods; moving targets; nonparametric methods; parametric methods; radar backscattering; radar image processing; radar imaging; radar signal processing; radar signals; signal representation; time-varying behavior; Backscatter; Fourier transforms; Image analysis; Image processing; Radar applications; Radar imaging; Radar signal processing; Signal analysis; Signal processing; Time frequency analysis;
