The detection of tonal signals with unknown frequencies is an important area of study in underwater signal processing. A common approach to address this issue is to use the Discrete Fourier Transform (DFT) for observations. When a tone does not lie precisely at the discrete DFT frequency point, its energy will leak to adjacent frequency point. This phenomenon is known as scalloping loss or Picket Fence Effect (PFE). PFE leads to the degradation of detection performance based on DFT. This paper studies the problem of robust detection in the case of PFE. A coherently-averaged power processor utilizing the information of adjacent frequency bins is designed. The results of simulations and experiments show that the proposed method is robust against PFE, and is highly suitable for tone detection in practical circumstances.

Over the last two decades, low-frequency active sonar has become an attractive tool for underwater target detection. The reverberation to signal ratio (RSR) of transmitted waveforms is an important factor affecting the detection capability of low-frequency active sonar. Therefore, reasonable waveform design for reverberation suppression of active sonar is an important topic. Pulse trains of linear frequency-modulated (PTFM) waveforms have been proposed and manifested their good performance in suppressing reverberation. The number of sub-pulses is positively related to the reverberation to signal ratio; the lower the number of sub-pulses, the lower the reverberation to signal ratio. However, to avoid ambiguity in a Doppler measurement, the PTFM waveforms have a requirement for the number of sub-pulses to be satisfied, which prevents its reverberation suppression performance from being further improved. In this paper, we propose a coprime pulse train of linear frequency-modulated (CPTFM) waveform, which reduces the number of sub-pulses to some extent. Therefore, the ability of reverberation suppression of the CPTFM waveform can be improved. The RSR was chosen as the metric to evaluate the waveform’s ability to suppress reverberation, and the theoretical formula for the RSR of the CPTFM waveform was derived in zone A and B. With the overlap of zones A and B brought about by the decrease in the number of sub-pulses, the average RSR of zones A and B is used in this paper to evaluate the reverberation suppression ability of the waveform. The simulation experiment shows that the proposed CPTFM waveform decreases the average RSR by 7 dB and 20 dB in comparison to the reference PTFM waveform and continuous waveform (CW), which is consistent with the theoretical results by the derived formulas.

In passive sonars, distance and depth estimation of underwater targets is often limited by the accuracy of time delay estimations. The estimation accuracy of the existing methods of time delay estimation is limited by the uniform discrete grid (signal sampling rate). When a true time delay is out of the grid, the estimation accuracy deteriorates due to the mismatch between the real-time delay and the discrete grid. This paper proposes a new method for time delay estimation, which realizes the time delay estimation under the framework of variational Bayesian inference. The proposed method is grid-less, that is, continuous in the time domain. Unlike the popular grid-less compressive time delay estimation method, this method does not require parameter adjustment, and can automatically estimate the number of time delays, noise variance, and amplitude variance. The simulation results showed that the performance of the proposed method was superior to the reference state-of-the-art time delay estimation methods.

Displaced phase center antenna (DPCA) micro-navigation has been widely applied in the motion compensation of synthetic aperture sonars (SASs). Estimating the time delay is the most important step for DPCA-based motion compensation. However, at present, the existing methods of estimating the time delay in motion compensation are not sufficiently accurate, which limits the improvement of imaging quality of SASs. This paper proposes a time delay estimation method using joint-sub-band phase unwrapping, which achieves much higher estimation accuracy than the reference method. The experimental results demonstrate that the proposed method dramatically improves the SAS imaging quality, compared to the reference method.

Communication in deep-sea shadow zones remains a significant challenge due to high propagation losses, complex multipath effects, long transmission delays, and strong environmental influences. In recent years, orthogonal chirp division multiplexing (OCDM) has demonstrated promising performance in underwater acoustic communication due to its robustness against multipath interference. However, its high peak-to-average power ratio (PAPR) limits its reliability and efficiency in deep-sea shadow-zone environments. This study applies a recently proposed generalized orthogonal chirp division multiplexing (GOCDM) modulation scheme to deep-sea shadow-zone communication. GOCDM follows the same principles as orthogonal signal division multiplexing (OSDM) while offering the advantage of a reduced PAPR. By segmenting the data signal into multiple vector blocks, GOCDM enables flexible resource allocation, optimizing the PAPR without compromising performance. Theoretical analysis and practical simulations confirm that GOCDM preserves the full frequency diversity benefits of traditional OCDM, while mitigating PARR-related limitations. Additionally, deep-sea experiments were carried out to evaluate the practical performance of GOCDM in shadow-zone environments. The experimental results demonstrate that GOCDM achieves superior performance under low signal-to-noise ratio (SNR) conditions, where the system attains a 0 bit error rate (BER) at 4.2 dB and 6.8 dB, making it a promising solution for enhancing underwater acoustic communication in challenging deep-sea environments.

Recently, the array-invariant method was proposed to passively localize sources of opportunity in shallow water. It exploits multiple arrivals which are different in terms of beam angle and travel time. Conventional plane-wave beamforming in the existing array-invariant method is used to obtain beam-time migration. The resolution capability of conventional plane-wave beamforming is determined by array aperture, which, however, limits the localization accuracy of the existing array-invariant method. To improve the localization accuracy, this study proposes the use of two-dimensional (2D) deconvolution to obtain a better beam-time migration than in conventional plane-wave beamforming. Our simulation with a small horizontal array showed that the range estimation error of the proposed array-invariant method based on 2D deconvolution was only one-third of that of the existing method. The experiment also demonstrated the validity of our proposed method.