Underwater acoustic signal analysis by multi-scaling and multi-translation wavelets

The underwater acoustic signals detected by a hydrophone can be separated into two categories, i.e., transient signals and stationary signals. Transient signals are hard to be detected but they could include important features for target identification. Recently the wavelet transform is considered as a good method to detect transient signals. However, the occurring time and the effective time-frequency product are asked to de determined before the wavelet transform can be successfully applied. In this paper, a multi-scaling wavelet is developed to cover signals with distinct time and frequency resolutions and hence makes the detection performance better. Furthermore, a multi-translation wavelet is designed to explore the characteristics of the transient signal. To illustrate the effectiveness of the new design method, some experiments are taken to perform by using simulation and recorded real underwater acoustic signals. Experimental results showed that the fusion of the two wavelets with pi(0) =5.3 and 50 can have better detection performance than traditional techniques. The resultant translation-spectrum graph showed that both the frequency and the repetition interval for the transient signal can be successfully detected.