Recognition method for biomimetic camouflage communication signal imitating cetacean click in underwater multipath channels

Abstract

Focusing on the need of biomimetic camouflage communication signal recognition in underwater multipath channels, we propose a recognition method for biomimetic camouflage click communication train (BCCCT) based on time delay difference (TDD) coding in multipath channels. For the problem of multipath interference, we perform multipath determination on the received signal by autocorrelation, filter relevant peak points, determine the time delays between multipaths, and remove the multipath interference signals according to the determined time delays. A click extraction method based on the double sliding window is proposed, which locates the boundary of click by signal envelope. By analyzing the distribution characteristics of the time interval of adjacent clicks (TIAC) of BCCCT and real click train (RCT), we model the TIACs based on Gaussian kernel probability density estimation (PDE), and recognize the BCCCTs by the Convolutional Neural Networks (CNN), which takes the PDE curve as the system input. The numerical simulations and a lake experiment are carried out to measure the effectiveness of the recognition method proposed under different signal-to-noise ratios (SNR), coding parameters, and channels. The recognition accuracy can achieve 80 % at 0 dB in the constructed channels. Moreover, in the real underwater communication environment, the recognition accuracy can achieve 95 %.