High-Sensitivity Detection Method for Weak Signals of Vessel Shaft-Rate Electric Field

There are weak signals in shaft-rate electric fields from vessels, and they are easily masked by noise. To address these issues, this paper proposed a comprehensive high-gain weak signal detection method guided by the priority detection and selective enhancement principle. First, complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) was combined with narrowband power spectrum energy peak entropy ratio(EPER) features. Then, sliding window and dynamic threshold techniques were used to detect the target signal. After successful detection, the proposed method triggered a tri-stable stochastic resonance and variable step-size least mean p-norm(VSS-LMP) enhancement mechanism to further enhance the spectral characteristics of the target signal, thereby enabling the extraction of the target signal’s characteristic frequency. Simulation results show that the proposed method achieves a detection accuracy rate exceeding 85% under a signal-to-noise ratio of −12 dB, with a false detection rate below 30%, and it can accurately extract the target signal’s characteristic frequency, providing a feasible technical approach for real-time monitoring of weak electric field signals from vessels.