Application of a sparse time-frequency technique for targets with oscillatory fluctuations

Abstract

In this paper, an application of the tunable Q-Factor wavelet transform (TQWT) to a maritime object classification problem is demonstrated. The TQWT, which depends on the two main parameters of the Q-factor and asymptotic redundancy, matches the oscillatory behaviour of the signal of interest when tuned. The approach, which differs from the Fourier and Wavelet transforms, decomposes a signal into a “high-Q-factor” and “low-Q-factor” component, and can be used to distinguish two radar range profiles of different oscillatory nature. The results of the paper show that the TQWT can provide sparse representation for some signals and that morphological component analysis (MCA) can be used to differentiate two radar signals based on their TQWT parameters.