Based on Adaptive Tunable Q-factor Wavelet Transform Target Detection Technology under Sea Clutter Background

In this paper, for the detection of slow and weak targets submersed in the sea clutter, by utilizing the difference between the oscillation characteristics of the sea clutter and the moving targets, a slow and weak target detection algorithm in the background of sea clutter based on the adaptive tunable Q-factor wavelet transform is proposed. Through iterative calculation and searching for the optimal ternary parameter combination that best matches the sea clutter and target oscillation characteristics, the morphological component analysis method is used to analyze the sea surface echo signal to obtain the optimal sparse representation of the target; then according to the proportion of each wavelet sub-band in the total energy of the target component, an appropriate threshold is selected to determine the reconstruction wavelet coefficient set, and thus the target signal can be effectively separated from the sea clutter. Finally, simulation experiments with measured data from IPIX are carried out to verify the effectiveness of the proposed method. Results show that the algorithm proposed in this paper can effectively detect the slow and weak target falling into the sea clutter Doppler channel without any prior information of targets and clutter.