With the development of artificial intelligence technology, visual simultaneous localization and mapping (SLAM) has become a cheap and efficient localization method for underwater robots. However, there are many problems in underwater visual SLAM, such as more serious underwater imaging distortion, more underwater noise, and unclear details. In this paper, we study these two problems and chooses the ORB-SLAM2 algorithm as the method to obtain the motion trajectory of the underwater robot. The causes of radial distortion and tangential distortion of underwater cameras are analyzed, a distortion correction model is constructed, and five distortion correction coefficients are obtained through pool experiments. Comparing the performances of contrast-limited adaptive histogram equalization (CLAHE), median filtering (MF), and dark channel prior (DCP) image enhancement methods in underwater SLAM, it is found that the DCP method has the best image effect evaluation, the largest number of oriented fast and rotated brief (ORB) feature matching, and the highest localization trajectory accuracy. The results show that the ORB-SLAM2 algorithm can effectively locate the underwater robot, and the correct distortion correction coefficient and DCP improve the stability and accuracy of the ORB-SLAM2 algorithm.

Meterage is an important action to ensure the performance of underwater acoustic positioning system, but the commonly used measurement methods are mostly based on the low degrees of freedom (DOF) measurement and control platforms which could not realize the all-round and high efficiency evaluation of this equipment. In this paper, we develop a new metering method base on the conventional standard 4-DOF measurement and control platform to realize the whole exploration space high efficiency and high accuracy measurement of underwater acoustic positioning systems in 6-DOF space. First, a 4-DOF space to 6-DOF space quantity value propagation model is proposed, and a rigorous mathematical expression is established. Next, a measurement procedure is formed based on the building of a standard base-line field, so the channel of transforming measurable position coordinate of the measured field point in 4-DOF space to the 6-DOF space is established. Finally, the evaluation of the measurement uncertainty is done using both the Guide to the expression of uncertainty in measurement method (GUM method) and Adaptive Monte Carlo method (AMCM method), and the evaluation results of GUM method are verified by AMCM method correspondingly, the effectiveness of this metering theory and the corresponding uncertainty evaluation methods are also illustrated by analyzing the length of coverage interval and numerical tolerances of measurement uncertainty. The research results show that the relative combined uncertainty of the metering system is not higher than 0.18% with the parameters given in this paper.

In this paper, a multimodal superposition model of the scattered acoustic field from a spherical target is investigated and the distribution laws of the scattered acoustic field of different sizes of rigid and elastic spheres at different frequencies are analyzed. The scattering cross section is approximated as the geometric projected area under the high-frequency/large-radius condition, whereas the scattering cross section is proportional to the fourth power of the frequency under the low-frequency/small-radius condition (ka ≪ 1). The scattering characteristics of the elastic sphere are affected by both geometric and elastic scattering, and the presence of Rayleigh and whispering-gallery waves significantly affects the acoustic field in the vicinity of the elastic sphere. Numerical simulation results show that the scattered acoustic field of the rigid sphere exhibits obvious directivity and geometric shadowing effects at high frequencies, while the distribution of the acoustic field of the elastic sphere exhibits complex interference phenomena and energy attenuation due to the elastic resonance waves. This study provides a theoretical basis and quantitative evaluation method for underwater target acoustic detection and identification.

Horizon picking underpins the interpretation of subbottom profile (SBP) data, acoustical inversion, and related applications. We present a horizon-picking method based on an improved wavelet multiresolution analysis. The approach uses low-resolution images from multiscale decomposition to track lateral layer continuity and combines nonmaximum suppression with hysteresis thresholding to achieve uninterrupted detection. A graph-based linking algorithm further refines edges and improves accuracy. To correct horizontal offsets and localization errors caused by phase distortion during wavelet reconstruction, we introduce a morphology-guided reconstruction strategy. Key parameters are determined in synthetic experiments and validated on field data. Compared with traditional approaches, the proposed method yields more continuous, accurate, and high-resolution horizons. The method’s effectiveness is demonstrated on SBP data acquired in Jiaozhou Bay.