Detection of transient signals by wavelet packet transform and stochastic resonance

Abstract

The problem of detecting an unknown transient signal in noise is considered. The observed data is first, quantized by a symmetric quantizer. By an optimum matching of the quantizer thresholds to the noise probability density function, the signal-to-noise ratio in the data is enhanced by the phenomenon of stochastic resonance. The output of the stochastic resonator (optimal quantizer) is then transformed using a translation-invariant wavelet packet transform (TIWPT). The magnitude of the maximum magnitude coefficient, in the entire TI-WPT decomposition is used as the test-statistic. Simulation results are presented to show that, at very low SNRs, the TIWPT detector preceded by the stochastic resonator gives a much better detection performance than a detector based on the TIWPT alone.