An Adaptive Dual-Channel Underwater Target Detection Method Based on a Vector Cross-Trispectrum Diagonal Slice

This paper introduces a method for detecting weak line spectrum signals in dynamic, non-Gaussian marine noise using a single vector hydrophone. The trispectrum diagonal slice is employed to extract coupled line spectrum features, enabling the detection of line spectra with independent frequencies and phases while effectively suppressing Gaussian noise. By constructing a cross-trispectrum diagonal slice spectrum from the hydrophone’s sound pressure and composite particle velocity, the method leverages coherence gain to enhance the signal-to-noise ratio (SNR). Furthermore, a discriminator based on the cross-coherence function of pressure and velocity is proposed, which utilizes a dynamic threshold to adaptively and in real-time select either the vector cross-trispectrum diagonal slice (V-TriD) or the conventional energy detection (ED) as the optimal detection channel for incoming signal. The feasibility and effectiveness of this method were validated through simulations and sea trial data from the South China Sea. Experimental results demonstrate that the proposed algorithm can effectively detect the target signal, achieving an SNR improvement of 3 dB at the target frequency and an average reduction in broadband noise energy of 1–2 dB compared to traditional energy spectrum detection. The proposed algorithm exhibits computational efficiency, adaptability, and robustness, making it well suited for real-time underwater target detection in critical applications, including harbor security, waterway monitoring, and marine bioacoustic studies.