The underwater electric field signal can be excited by underwater vehicles, such as the shaft-rate electric field and the corrosion electric field. The electric field signature of each vehicle exhibits significant differences in time and frequency domain, which can be exploited to determine target positions. In this paper, a novel passive localization method for underwater targets is presented, leveraging a uniform linear electrode array (ULEA). The ULEA manifold along the axial direction is derived from the electric field propagation in an infinite lossy medium, which provides the nonlinear mapping relationship between the target position and the voltage data acquired by the ULEA. In order to locate the targets, the multiple signal classification (MUSIC) algorithm is applied. Then, capitalizing on the rotational invariance of matrix operations and exploiting the symmetry inherent in the ULEA, we streamline the six-dimensional spatial spectral scanning onto a two-dimensional plane, providing azimuth and distance information for the targets. This method significantly reduces computational overhead. To validate the efficacy of our proposed method, we devise a localization system and conduct a simulation environment to estimate targets. Results show that our method achieves satisfactory direction and reliable distance estimations, even in scenarios with low signal-to-noise ratios.

The localization process of the underwater electric dipole source involves solving the global optimal solution of a nonlinear function, which necessitates a multidimensional search and remarkable computational resources. Challenges including slow solution speed and the risk of missing the global optimal solution also exist. To address these challenges, in this study, a global search and localization method based on normalized electric field amplitude, which simultaneously matches and solves the target source position and dipole moment, is proposed. Moreover, the particle swarm optimization (PSO) algorithm is integrated with the gravitational search (GSA) algorithm to propose the improved time-varying inertia-weighted PSO and GSA hybrid optimization algorithm (TVIW-PSO-GSA), enabling rapid optimization and solution of underwater electric dipole source localization. The proposed algorithm exhibits strong convergence capabilities while ensuring local search accuracy. The simulation results reveal that the proposed algorithm achieves faster convergence speed and more accurate estimation performance when compared with traditional optimization algorithms.

Autonomous underwater vehicles (AUV) have been increasingly employed in marine resource exploration and development tasks; however, maintaining of long-term operations requires energy supplementation, which mandates docking with platforms. To address the challenges of AUV docking in intricate oceanic environments, this study proposes a novel docking guidance solution, grounded in the rotating current field mechanism. This approach employs multiple pairs of dipoles to transmit fixed phase difference signals, thereby creating a stable and uniform low-frequency current field region. Furthermore, based on the signal amplitude and phase characteristics relative to position, this paper introduces three AUV docking guidance methods able to achieve precise positioning and expedite the docking process. Experimental findings demonstrate that the proposed docking guidance method offers notable advantages in terms of positioning accuracy and feasibility of implementation, thus presenting a novel technical avenue for AUV underwater docking guidance.

The widely use of electromagnetic waves to realize sea-ice-air across-media propagation information is important for the research in fields such as integrated sea-air-sky communication networks. This paper establishes the electromagnetic wave sea-ice-air across-media propagation model based on the CST Studio Suite 2019 simulation software, and uses the heterogeneous parallel numerical computing technology of Graphic Processing Unit (GPU) to perform the simulation calculation. A sea-ice-air model is established to compare with the sea-air model, and the propagation characteristics of the electric dipole radiation field across the medium at different frequencies and depths in the Very Low Frequency (VLF) band are studied. The results show that the electric dipole radiation field across the sea-ice-air medium is more attenuated than that across the sea-air medium, which more accurately simulates the electromagnetic wave transmission across the medium in the real marine environment.

This work, a new kernel affine projection algorithm called q-Rényi kernel-affine-projection-maximum correntropy-criterion (qKAPMCC) is proposed. The qKAPMCC algorithm is different from the traditional kernel affine projection algorithm: the cost-function for learning algorithm is derived by the correntropy-criterion, and the q-Rényi kernel function replaces the Gaussian kernel in RKHS. The qKAPCC have an outperformance in the NCE under the impulse-noise. Simulation in different non-Gaussian noise environments express high performance of the proposed qKAPMCC algorithm compared to other kernel adaptive filters.