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To design high-level control structures efficiently, reasonable mathematical model parameters of the vessel have to be known. Because sensors and equipment mounted onboard marine vessels can change during a mission, it is important to have an identification procedure that will be easily implementable and time preserving and result in model parameters accurate enough to perform controller design. This paper introduces one such method, which is based on self-oscillations (IS-O). The described methodology can be used to identify single-degree-offreedom nonlinear model parameters of underwater and surface marine vessels. Extensive experiments have been carried out on the VideoRay remotely operated vehicle and Charlie unmanned surface vehicle to prove that the method gives consistent results. A comparison with the least-squares identification and thorough validation tests have been performed, proving the quality of the obtained parameters. The proposed method can also be used to make conclusions on the model that describes the dynamics of the vessel. The paper also includes results of autopilot design in which the controllers are tuned according to the proposed method based on self-oscillations, proving the applicability of the proposed method. C