The echo of shipborne high-frequency surface wave radar (HFSWR) is modulated by six-degrees-of-freedom (6-DOF) motion, affecting the detection of the target and the remote sensing of ocean surface dynamics parameters. Commonly, motion compensation methods of shipborne HFSWR describe each aspect of the 6-DOF motion as the superposition of sinusoidal motion, which results in the effect of motion compensation affected by the precision of 6-DOF motion parameters. A motion compensation method based on dual reference radio frequency (RF) signals is proposed in this paper, without depending on a sinusoidal motion model to describe the 6-DOF motion. By using the motion compensation parameters, which are relevant to the motion attitude and calculated from the information of dual reference RF signals located onshore, the method realizes the compensation of shipborne HFSWR echo modulated by platform 6-DOF motion. This paper proposes the extraction of reference RF signals from radar echo and analyzes the influence of the location of the reference RF signals’ emission source on the motion compensation method. The result shows that a good motion compensation effect is achieved in eliminating the influence of 6-DOF motion modulation. In addition, a traversal of different reference RF signals’ emission source locations is conducted, and the simulation results show that the method proposed in this paper has universality.

The yaw-angle signal output by shipboard attitude sensors (e.g., inertial navigation systems) is a composite of the heading and wave-induced yaw (WIY). The heading reflects large-scale directional changes due to maneuvering or voyage planning, exhibiting slowly varying, trend-like characteristics; WIY is the oscillatory motion caused by random wave–hull interaction, approximately following a zero-mean normal distribution. Accurately and adaptively separating these two components from the composite yaw-angle signal is a key technical challenge in ship motion monitoring or wave parameter inversion. This paper proposes a heading–WIY separation method based on Empirical Mode Decomposition (EMD) and multi-dimensional physical–statistical evaluation. The method adaptively decomposes the composite yaw signal via EMD and automatically determines the optimal mode combination through statistical evaluation. Moreover, a short-time segment processing strategy and overlap-region continuity checks are introduced to overcome heading trend variations over long time scales. The method is validated using a multi-scenario simulation dataset encompassing four conditions and various sea states, as well as at-sea collected data. Results demonstrate high extraction accuracy without requiring a system dynamics model or scenario-specific parameter tuning across all conditions. And the proposed method performs better in comparison to the conventional methods, particularly under conditions of spectral overlapped or high sea states.