Oil spills generate a large cost in environmental and economic terms. Their identification plays an important role in oil-spill response. We propose an oil spill detection method with improved adaptive enhancement on X-band marine radar systems. The radar images used in this paper were acquired on 21 July 2010, from the teaching-training ship “YUKUN” of the Dalian Maritime University. According to the shape characteristic of co-channel interference, two convolutional filters are used to detect the location of the interference, followed by a mean filter to erase the interference. Small objects, such as bright speckles, are taken as a mask in the radar image and improved by the Fields-of-Experts model. The region marked by strong reflected signals from the sea’s surface is selected to identify oil spills. The selected region is subject to improved adaptive enhancement designed based on features of radar images. With the proposed adaptive enhancement technique, calculated oil spill detection is comparable to visual interpretation in accuracy.

Anchor penetration is an important issue involved in the study of submarine pipeline damage accidents. To explore the penetration of a ship’s anchor under certain conditions, this study investigated the motion and force of an anchor and formulated a calculation method for the bottoming speed of an anchor. Meanwhile, the depth of anchor penetration was calculated under different conditions according to bottoming speed through programming. Finally, the reliability of the calculation method for the penetration depth was verified by comparing the actual measurement and the numerical simulation. On the basis of the findings, the calculation results were further analyzed, and conclusions were derived regarding the relationship between anchor mass, the horizontal projected area of the anchor, the anchor height on the water surface, and water depth. The conclusions provide suggestions for the application of anchor penetration in terms of seabed depth with certain reference values.