In this study, we investigate the feasibility of using historical remote sensing data to predict the future three-dimensional subsurface ocean temperature structure. We also compare the performance differences between predictive models and real-time reconstruction models. Specifically, we propose a multi-scale residual spatiotemporal window ocean (MSWO) model based on a spatiotemporal attention mechanism, to predict changes in the subsurface ocean temperature structure over the next six months using satellite remote sensing data from the past 24 months. Our results indicate that predictions made using historical remote sensing data closely approximate those made using historical in situ data. This finding suggests that satellite remote sensing data can be used to predict future ocean structures without relying on valuable in situ measurements. Compared to future predictive models, real-time three-dimensional structure reconstruction models can learn more accurate inversion features from real-time satellite remote sensing data. This work provides a new perspective for the application of artificial intelligence in oceanography for ocean structure reconstruction.

Satellite remote sensing enables the extensive, long-term observation of oceanic changes. To achieve transparent ocean observation, artificial intelligence is innovatively used to reconstruct the three-dimensional ocean structure from remote sensing data with spatiotemporal attention. However, high-resolution satellite imagery imposes high computational demands. This study proposes Spatiotemporal Window Ocean (SWO), which is an efficient network that uses a special calculation strategy and spatiotemporal window attention to reduce complexity. The model integrates multiple satellite data sources, including sea surface temperature (SST), absolute dynamic topography (ADT), and sea surface salinity (SSS). Our experimental results demonstrate that SWO achieves lower computational costs and superior performance compared with recent commonly used spatiotemporal sequence models. Specifically, SWO requires a training time equivalent to 1/3 of SimVP, 1/4 of PredRNN, and 1/5 of SA-ConvLSTM while achieving a root mean square error (RMSE) index that is 13.8%, 20.3%, and 13.2% better, respectively. The computational advantages of SWO offer an important technical means for the high-resolution reconstruction of ocean phenomena in the future.

Three-dimensional hydro-acoustic imaging is a research hot spot in the underwater acoustic signal processing field, which has a wide range of application prospects in marine environmental resource surveying, seabed topography and geomorphological mapping, and underwater early warning and monitoring. To solve the problem that the resolution of the current imaging sonar reduces rapidly with increase in distance and a scanning gap exists in side-scan sonar, we designed a down-looking 3D-imaging sonar with a linear array structure. The imaging scheme adopts a time-domain spatial beam-forming method with the Back Projection (BP) algorithm as the core, and the formation of a virtual plane array can effectively improve the along-track resolution. To cope with the interference of the carrier motion error on the imaging, we proposed a high-precision sub-wavelength motion compensation method based on a real-time acoustic calibration system. Simulation and real data experiments show that the motion compensation method can effectively eliminate the influence of motion error and make the imaging energy more focused, leading to higher-quality acoustic images. Under equal average energy, the maximum superimposed sound intensity values in the imaging results increased by 20.75 dB and 6.57 dB, respectively, for simulation and real data. After motion compensation, the resolution of this imaging system reached 3 cm × 3 cm × 2.5 cm @ Depth = 17 m, TBP = 30 s · Hz.

A horizontal suspension hydrophone line array system for deep water target detection is demonstrated. Theoretical estimation of the array shapes at different array states is fulfilled through detailed kinetic analysis. When steady ocean forces solely exert on the array system from three orthogonal directions and the array is in the neutral-buoyancy state, the array shapes are parabola linetypes. When no ocean forces exert on the array system and the array is in the non-neutral buoyancy state, the static array shapes are catenary linetypes. The simulation results can guide the curve fitting process of the array shape estimation based on depth and attitude sensors.

A separate type fiber optic vector hydrophone (FOVH) based on FBG accelerometers is designed and tested. The experimental results show that the average acceleration sensitivities are −18 dB re rad/g, the background noises are −70 dB re rad/√Hz, and an unambiguous ‘8’ shape directivity is obtained at 315 Hz.

Resonator structures with a multiwavelength filter are critical devices for the fabrication of stable output multiwavelength fiber lasers. In this study, we propose a spatially separated multiwavelength filter based on a 2D chirped fiber grating. The resonant fields of lasers with different wavelengths are spatially separated, reducing cross-gain modulation. In addition, the structure of the 2D chirped fiber grating is analyzed, and the spectral output characteristics of the device are investigated for different grating parameters, which provides theoretical guidance for designing such a novel optical comb filter. Furthermore, by fabricating the 2D chirped fiber grating onto a single-mode fiber, a multiwavelength filter with 17 wavelengths, a frequency interval of approximately 88 GHz, and a grating length of 4.8 cm is created. This device is characterized by its compact structure and simple fabrication method.