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Infrared and visible image fusion is a very effective way to solve the degradation of sea images for unmanned surface vessels (USVs). Fused images with more clarity and information are useful for the visual system of USVs, especially in harsh marine environments. In this work, three novel fusion strategies based on adaptive weight, cross bilateral filtering, and guided filtering are proposed to fuse the feature maps that are extracted from source images. First, the infrared and visible cameras equipped on the USV are calibrated using a self-designed calibration board. Then, pairs of images containing water scenes are aligned and used as experimental data. Finally, each proposed strategy is inserted into the neural network as a fusion layer to verify the improvements in quality of water surface images. Compared to existing methods, the proposed method based on adaptive weight provides a higher spatial resolution and, in most cases, less spectral distortion. The experimental results show that the visual quality of fused images obtained based on an adaptive weight strategy is superior compared to other strategies, while also providing an acceptable computational load.

In the field of USV autonomous control system design, redundant design technology is the important method to improve system reliability. In order to solve the problem of insufficient reliability when USV carrying out long endurance and open sea task, this paper analyzes the critical design elements of autonomous control system redundant configuration, presents a high reliable hybrid redundant structure for USV autonomous control system, and realizes redundant strategy and fault-tolerant control. This paper forms the USV autonomous control system redundant configuration scheme comply with the fault-tolerant capability and redundant rank of USV autonomous control system. Redundancy management strategies and algorithms are used to implement USV autonomous control based on hybrid redundant design. The reliability analysis and computation validate task reliability of the autonomous control system based on hybrid redundant structure.

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