Ultra-Wideband Radar Transient Detection using Time-Frequency and WaveletTransforms

摘要

Detection of weak ultra-wideband (UWB) radar signals embedded in non-stationaryinterference presents a difficult challenge. Classical radar signal processing techniques such as the Fourier transform have been employed with some success. However, time-frequency distributions or wavelet transforms in non-stationary noise appears to present a more promising approach to the detection of transient phenomena. In this thesis, analysis of synthetic signals and UWB radar data is performed using time-frequency techniques, such as the short time Fourier transform (STFT), the Instantaneous Power Spectrum and the Wigner-Ville distribution, and time-scale methods, such as the a trous discrete wavelet transform (DWT) algorithm and Mallat's DWT algorithm. The performance of these methods is compared and the characteristics, advantages and drawbacks of each technique are discussed.