To acquire the enhanced underwater ship-radiated noise signal in the presence of array shape distortion in a passive sonar system, the phase difference of the line-spectrum component in ship-radiated noise is often exploited to estimate the time-delay difference for the beamforming-based signal enhancement. However, the time-delay difference estimation performance drastically degrades with decreases of the signal-to-noise ratio (SNR) of the line-spectrum component. Meanwhile, although the time-delay difference estimation performance of the high-frequency line-spectrum components is generally superior to that of the low-frequency one, the phase difference measurements of the high-frequency line-spectrum component often easily encounter the issue of modulus 2$\pi$ ambiguity. To address the above issues, a novel time-frequency joint time-delay difference estimation method is proposed in this paper. The proposed method establishes a data-driven hidden Markov model with robustness to phase difference ambiguity by fully exploiting the underlying property of slowly changing the time-delay difference over time. Thus, the phase difference measurements available for time-delay difference estimation are extended from that of low-frequency line-spectrum components in a single frame to that of all detected line-spectrum components in multiple frames. By jointly taking advantage of the phase difference measurements in both time and frequency dimensions, the proposed method can acquire enhanced time-delay difference estimates even in a low SNR case. Both simulation and at-sea experimental results have demonstrated the effectiveness of the proposed method.

In the presence of multiple sources, the performance of direction-of-arrival (DOA) estimation based on beam power maximization is susceptible to the energy leaking from the interference beams to the target beam, especially in the case that the signal of interest (SOI) is quite weak. To address this issue, a robust wideband DOA estimation method is proposed in this paper. Unlike those conventional high-resolution methods which mitigate the influence of energy leakage by reducing beamwidths and sidelobe levels, the proposed method achieves this by directly reconstructing the element-space data to approach the received hydrophone data of the single-source scenario containing only the SOI. Element-space data reconstruction (ESDR) for the SOI is achieved by removing the element-space waveforms of all the interference signals from the received hydrophone data. Moreover, an iterative algorithm is developed to adaptively extract the element-space waveform of each interference signal, without requiring the prior information of the array amplitude response coefficients and hydrophone coordinates of a distorted towed array. Simulation results show that the proposed method outperforms its counterparts in terms of estimation accuracy for a multi-source scenario. Meanwhile, the DOA estimation performance of the proposed method in a multi-source environment is close to that obtained by the beam power maximization method in the single-source scenario, even if the signal-to-interference ratio (SIR) is as low as −25 dB. At-sea experimental results prove that, even though the number of signal sources is as many as seven and the SOI is contaminated by real ocean ambient noise, the proposed method still achieves a better DOA estimation performance compared to existing state-of-the-art methods.

This paper proposes a method for visualizing three-dimensional non-uniformly sampled data from multibeam echosounder systems (MBESs), aimed at addressing the requirements of monitoring complex and dynamic underwater flow fields. To tackle the challenges associated with spatially non-uniform sampling, the proposed method employs linear interpolation along the radial direction and arc length weighted interpolation in the beam direction. This approach ensures consistent resolution of three-dimensional data across the same dimension. Additionally, an opacity transfer function is generated to enhance the visualization performance of the ray casting algorithm. This function leverages data values and gradient information, including the first and second directional derivatives, to suppress the rendering of background and non-interest regions while emphasizing target areas and boundary features. The simulation and experimental results demonstrate that, compared to conventional two-dimensional beam images and three-dimensional images, the proposed algorithm provides a more intuitive and accurate representation of three-dimensional data, offering significant support for the observation and analysis of spatial flow field characteristics.

Accurate Doppler-factor estimation and effective Doppler compensation are essential for reliable high-data-rate mobile underwater acoustic communication. However, false correlation peaks and missed peak detections can degrade estimation accuracy or lead to estimation failure. To address the above problem, this paper proposes a coarse-to-fine Doppler-factor estimation method that combines replica correlation, periodic-spacing-based false-peak discrimination, and multi-interval refinement. First, the received signal is cross-correlated with a bank of Doppler-scaled replicas of the synchronization waveform to mitigate mismatch and obtain a coarse Doppler estimate. The Doppler-scaled synchronization-header spacing can be acquired based on the coarse estimate, enabling false correlation peaks to be identified and rejected through integer-multiple spacing-consistency tests. Exploiting the inherent integer-multiple structure of the Doppler-scaled synchronization-header spacings, the proposed method then combines the retained pairwise peak intervals using a Gauss–Markov-type weighted least-squares (WLS) estimator to obtain a refined Doppler-factor estimate in closed form. By exploiting the known multi-header timing structure and jointly incorporating multiple interval measurements, the method limits the influence of false correlation peaks and reduces sensitivity to individual peak-position errors, thereby improving the accuracy of Doppler-factor estimation. Numerical comparisons with representative existing Doppler-factor estimation methods demonstrate that the proposed method achieves favorable estimation accuracy over the investigated signal-to-noise-ratio and radial-velocity ranges. Further simulations demonstrate the robustness of the proposed method to noise-induced false correlation peaks. Comparative sea-trial results show that the proposed estimates generally remain close to the navigation-derived reference, providing further evidence of the effectiveness of the proposed method under the tested field conditions.