An Improved Cohen-Class Based Extraction Method for Fine Spectral Feature of Line Spectrum From Ship-Radiated Noise

Abstract

The line spectrum from ship-radiated noise is a critical feature for passive sonar to detect underwater acoustic targets. However, due to weak target strength as well as severe propagation attenuation and oceanic ambient noise, the signals received by passive sonars generally manifest low signal-to-noise ratio (SNR), strong nonstationarity and overwhelmed Doppler-shifted line spectrum. These challenges deteriorate the performance of conventional Cohen class time frequency distribution (CCTFD) methods in capturing the fine spectral feature of such signals. To overcome these difficulties, this research proposes an improved Cohen-class method, termed ambiguity function-instantaneous autocorrelation function joint filtering Wigner–Ville distribution (AIJF-WVD). First, this study analyses how standard CCTFD's cross-term suppression mechanism degrades time-frequency resolution/concentration in time-frequency distribution (TFD) when processing multicomponent Doppler-shifted signals. Departing from conventional framework of cross-term suppression via two-dimensional low-pass filtering along both frequency-shift dimension and time-delay dimension in ambiguity function (AF) domain, AIJF-WVD presents a novel joint filtering approach that consists of designing one-dimensional finite impulse response (FIR) filter solely along frequency-shift dimension in AF domain (while maintaining time-delay dimension unchanged) as well as subsequent one-dimensional low-pass filtering along time dimension in instantaneous autocorrelation function (IAF) domain based on the designed filter. Therefore, this novel method enhances TFD performance of cross-term suppression and frequency resolution simultaneously while maintaining low computational complexity. Then, the performances of various CCTFD methods are quantitatively assessed using mean structural similarity (MSSIM), normalised Rényi entropy (NRE), half-power bandwidth (HBW) and mean runtime. Finally, the global spectral estimation accuracy of Doppler-shifted tonals is evaluated through tracking deviation analysis. Compared to conventional CCTFDs, AIJF-WVD exhibits superior robustness and adaptability in low-SNR background noise as evidenced by processing both simulated signals and ship-radiated noise from sea trials. Furthermore, the refined approach is also validated to significantly improve cross-term suppression, time-frequency concentration and computational efficiency characteristics while preserving frequency resolution and superior tonal trajectory tracking capability for passive sonar.