The problem of determining the parameters of variational mode decomposition (VMD) is analyzed, and a sea clutter denoising method based on optimized variational mode decomposition (VMD) is proposed. The whale optimization algorithm (WOA) was used to optimize the number of modes K and penalty parameters, and the original sea clutter signal was decomposed adaptively to remove the modal component with low variance contribution rate (VCR). The modal component dominated by noise was screened by combining with fuzzy entropy and processed by Savitzky-Golay (SG) filtering. The least square support vector machine (LSSVM) was used to predict the sea clutter signal and verify the denoising effect for the signal reconstructed by superposition of filtered component and useful component. Simulation results show that the proposed algorithm can effectively suppress noise interference, and the root mean square error (RMSE) after denoising is 0. 000 29, which is two orders of magnitude lower than the root mean square error (RMSE) before denoising is 0. 012 3.