Search Results (4)

In this study, we propose a novel method for retrieving the three-dimensional (3D) wave surface from sea clutter using both simulated and measured data. First, the linear wave superposition model and modulation principle are employed to generate simulated datasets comprising 3D wave surfaces and corresponding sea clutter. Subsequently, we develop a Pix2Pix model enhanced with a self-attention mechanism and a multiscale discriminator to effectively capture the nonlinear relationship between the simulated 3D wave surfaces and sea clutter. The model’s performance is evaluated through error analysis, comparisons of wave number spectra, and differences in wave surface reconstructions using a dedicated test set. Finally, the trained model is applied to reconstruct wave surfaces from sea clutter data collected aboard a ship, with results benchmarked against those derived from the Schrödinger equation. The findings demonstrate that the proposed model excels in preserving high-frequency image details while ensuring precise alignment between reconstructed images. Furthermore, it achieves superior retrieval accuracy compared to traditional approaches, highlighting its potential for advancing wave surface retrieval techniques. Full article

As devastating natural disasters, typhoons pose a tremendous threat to human society, making effective typhoon early warning and monitoring crucial. To address this challenge, High Frequency Surface Wave Radar (HFSWR), which can observe oceanic parameters such as typhoon wind fields in real time and even capture the dynamic changes in the ionosphere, has become an effective tool for typhoon monitoring. This paper investigates the interaction mechanisms about Typhoon-Acoustic Gravity Waves (AGWs)-Ionosphere, as well as Typhoon-Ocean Waves for HFSWR, and simulates these interaction processes within HFSWR. Then a typhoon early warning and monitoring scheme for HFSWR has been proposed: In the first stage, the S-shaped ionospheric disturbances observed by HFSWR are utilized as precursor signals for early typhoon warnings. In addition, the second stage involves analyzing changes in first-order oceanic echo spectral peak ratio to pinpoint when the typhoon eye enters the radar detection range, thus initiating the typhoon monitoring phase. Subsequently, the measured data from HFSWR collected during Typhoon “Muifa” (2212) in conjunction with the proposed scheme are evaluated in detail. The results indicate that AGWs generated by typhoons can propagate into non-typhoon areas within the detection range, causing S- shaped ionospheric disturbances and providing approximately 6 h of early warning. At around 8:05 (UTC+8), an increasing trend in the first-order spectral peak ratio was noted, indicating the entry of the typhoon eye into the detection range, which closely aligns with the official typhoon path and marks the transition to the monitoring phase. The proposed scheme is expected to enhance the capability for typhoon early warning and real-time monitoring in specific sea areas and mitigate the risks associated with typhoon-related disasters. Full article

This paper presents a forward modeling method for the scattering center (SC) model of dynamic ships on time-varying sea surfaces, tailored for remote sensing and target-recognition applications. Grounded in ship hydrodynamics, the methodology delineates ship movements amidst fluctuating waves, harnessing computer graphics to integrate ship–sea geometries across diverse temporal instances. Utilizing the four-path model, the composite scattering effects are segregated into distinct ship and sea contributions, along with their mutual interactions. Augmented by high-frequency electromagnetic principles, the paper quantifies and deduces SC parameters, culminating in a 3-D parameterized SC model for complex maritime targets. Unlike conventional inverse methods, this approach employs a “cause-to-effect” forward strategy, establishing clear links between SCs and local geometries, enhancing the model’s physical clarity. Using the fishing ship as a case, this research compared the normalized similarity index and position-matching rate between the reconstructed synthetic aperture radar (SAR) image and the simulated SAR image. The results indicate that all computed results exceeded 90%. Furthermore, a comparison was conducted between the reconstructed radar cross-sections (RCS) obtained by expanding the model within a large angular range and the simulated results. The root mean square error between the two was less than 3 dB, affirming the accuracy and effectiveness of the proposed model. Additionally, the research examines the variations in SCs during the six-degrees-of-freedom motions, providing a detailed quantitative analysis of their temporal trends in amplitude and position. In summary, this investigation furnishes an efficient and economical framework for rapid radar characterization in dynamic, variable marine environments, fostering advancements in remote sensing and maritime target identification. Full article

The CBATS (carrier-based aircraft take-off and landing training system) is an important application of virtual reality technology in the simulation field. Large-scale, real-time ocean simulations are the biggest challenge to the authenticity of the visual system of CBATS and are also currently the main research hotspot in the field of computer graphics. In this paper, a hybrid Ocean Modeling Method based on wavelet transform is presented. This method introduces an accurate phase calculation and a wind-field model solution to compensate for the randomness of wave generation and the lack of physical mechanism in spectral methods. The computational cost is greatly reduced by using a rough spatial grid to calculate the amplitude and phase values at any point in space, which effectively avoids Nyquist–Shannon Theorem limitations caused by the numerical solutions of PDEs (partial differential equations), and a high-fidelity simulation of high frequency, detailed sea surface and coherent phase-dependent wave effects is achieved. Practical verification shows that the method can fully meet the real-time simulation training requirements of CBATS with a strong real-time performance and good stability. Thus, it could play a significant role in improving the performance of the visual system. Full article