Unmanned boats, while navigating at sea, utilize active compensation systems to mitigate wave disturbances experienced by onboard instruments and equipment. However, there exists a lag in the measurement of unmanned boat attitudes, thus introducing unmanned boat motion attitude prediction to compensate for the lag in the signal acquisition process. This paper, based on the basic principles of waves, derives the disturbance patterns of waves on unmanned boats from the wave energy spectrum. Through simulation analysis of unmanned boat motion attitudes, motion attitude data is obtained, providing experimental data for subsequent work. A combined prediction model based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Particle Swarm Optimization (PSO), and Support Vector Machine (SVM) is designed to predict the motion attitude of unmanned boats. Simulation results validate its superior prediction accuracy compared to traditional prediction models. For example, in terms of mean absolute error, it improves by 17% compared to the EMD-PSO-SVM model.

One of the most important but generally overlooked missions of the U.S. Navy is port security. While incidents in peacetime are generally rare, the 2000 terrorist attack on the destroyer USS Cole remains a real danger. Now the Navy is experimenting with using one of its newest unmanned boats as a way to protect warships sitting pierside from attack. In October 2000, the guided-missile destroyer USS Cole was refueling at the port of Aden in Yemen when it came under attack by Al Qaeda terrorists. A small boat loaded with explosives sidled up to the 10,000 ton destroyer and exploded, killing 17 U.S. Navy sailors and injuring 39.