Research on Comprehensive Detection Methods for Weak Signals in Underwater Target Shaft Frequency Electric Fields

To address the issue of weak target signals that are easily masked by noise in the detection of ship shaft frequency electric field signals, this paper proposes an electric field signal detection method based on the principle of ‘priority detection and selective enhancement.’ First, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is combined with narrowband power spectrum energy peak entropy ratio (EPER) features. Then, sliding window and dynamic threshold techniques are used to detect the target signal. After successful detection, the proposed method triggers 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 can accurately extract the target signal's characteristic frequency, providing a feasible technical approach for real-time monitoring of weak electromagnetic field signals from ships.