Ocean internal waves (IWs), induced by density stratification and fluid perturbations, are significant oceanic phenomena prevalent across global oceans, profoundly impacting marine environments and engineering safety. Although one-stage object detection models are favored in practical applications due to their efficient inference, they often suffer from insufficient accuracy in IW detection tasks. To address this, we introduce a novel one-stage, anchor-free detection approach based on Transformer for IW detection, proposing a new algorithm named IW-D-FINE, which balances detection accuracy and inference efficiency. On the public SAR dataset, IW-D-FINE achieves an AP@0.5 of 90.5, significantly outperforming existing one-stage methods while maintaining faster inference speeds than mainstream two-stage models. Furthermore, to mitigate the scarcity of internal wave samples, we construct a small-scale IWs dataset, YH3-IW-2025, and validate the algorithm thoroughly on this dataset. Experimental results demonstrate that IW-D-FINE exhibits robust performance under complex background interference, highlighting its application potential and scalability in IW detection tasks.

Precise vessel trajectory prediction is of great importance to the maritime safety. However, most of the existing methods only utilize Automatic Identifica

The motion characteristics are limited in a 3-DOF driving simulator using a classical washout algorithm, which results in unrealistic simulation effects. To address the issue, this paper proposes a Washout Algorithm for the 3-DOF driving simulator based on Feature Enhancement and Attitude Smoothing (FEASWA). Firstly, to enhance the coherence and realism of the motion, a Feature Enhancement Washout Algorithm (FEWA) for 3-DOF driving simulators is proposed. The algorithm coordinates the input and output attitude features to achieve dynamic simulation for the 3-DOF driving simulator. Secondly, the data smoothing technique based on Locally Weighted Scatterplot Smoothing (Loess) is designed since the classic washout algorithm does not account for the motion characteristics of the servomotor. It can reduce unnecessary stretching of the motor, improve its response within a confined space speed, and decrease instability during driving manoeuvres by smoothing the servomotor motion curve. The experimental results indicate that the proposed feature enhancement and attitude smoothing-based 3-DOF driving simulator washout algorithm can enhance the stability of the 3-DOF driving simulator motion and the platform spatial utilization efficiency with 40.1% than one of the classical washout algorithm.