Time-frequency analysis in radar backscatter problems.

Abstract

Time-frequency techniques provide new and unique insights for analyzing electromagnetic scattering problems. These techniques transform functions of time or frequency into two dimensional functions of both time and frequency to reveal non-stationary characteristics of the signal. The theory developed herein justifies applying the frequency-time transform to wide bandwidth signals illuminating stationary targets. The frequency-time representation of the return provides more information about the target and the scattering than regular Fourier analysis. Along with the position of the scattering centers, frequency-time analysis gives insights on the target's composition and configuration. In addition, the performance of these transforms when applied to noise are examined and quantified. The statistics of a Cohen's class time-frequency transformation are derived and verified numerically. Applying the time-frequency techniques to sampled continuous-wave radar data from a dynamic target provides insight into target motion and generate estimates of the target parameters. After considering a figure of merit for evaluating the time-frequency distribution, a customized kernel, determined using a genetic algorithm, is used to improve the performance of the standard spectrogram, the Wigner distribution, and the binomial distribution.