Underwater spectral line enhancement and transient interference suppression based on constrained non-negative matrix factorization

Abstract

Spectral line enhancement and transient interference suppression of underwater objects are critical issues for passive sonar systems. Conventional approaches for processing spectral lines have focused on either time-domain or frequency-domain methods. In this study, the constrained non-negative matrix factorization is proposed to process the underwater spectral lines in the joint time-frequency domain. Based on the sparsity of spectral lines in the frequency domain, the sparseness criterion is utilized to constrain the basis matrix that represents the frequency-mode of the signal. The correlation between sparsity and frequency estimation accuracy is examined with weight coefficients, and an effective weight coefficient interval for the sparseness term is determined to optimize the detection of the spectral line. To address the issue of abrupt changes in signal energy caused by transient interference, the temporal continuity criterion is applied to constrain the coefficient matrix representing the temporal gain mode of the signal. An analysis is conducted to determine the impact of weight coefficient on the continuity of the coefficient matrix, and the optimal weight coefficient of the temporal continuity term is established to suppress local transient strong interference. Experimental results demonstrate that the algorithm significantly enhances the capacity for the detection and extraction of spectral lines.