Extraction method of weak underwater acoustic signal based on the combination of wavelet transform and empirical mode decomposition

When studying underwater acoustic exploration, tracking and positioning, the target signals collected by hydrophones are often submerged in strong intermittent noise environmental noise. In this paper, an algorithm that combines empirical mode decomposition wavelet transform is proposed to achieve efficient extraction of environment with First calibration baseline drift performed on algorithm, then it decomposed into different intrinsic functions via mode. The threshold processing conducted according correlation coefficient each component original signal, finally reconstructed. simulation experiment results show compared conventional method method, when signal-to-noise ratio low there exist high-frequency jamming drift, combined can better extract laying foundation for direction-of-arrival estimation positioning next step.