Sea clutter hybrid denoising algorithm based on VMD

Abstract

In order to improve the detection accuracy of sea clutter wavelet prediction model further, a sea clutter hybrid denosing algorithm based on variational modal decomposition (VMD) is proposed. The VMD is adopted to decompose the sea clutter signal into a finite number of intrinsic modal functions (IMF) with limited bandwidths of different center frequencies. Then, we analyze the auto-correlation property of the decomposed signal and perform wavelet hard threshold filtering on the modal component with noise characteristics. Reconstructing the filtered component and the residual component to obtain a denosied signal. The sea clutter prediction model based on LSSVM is adopted to verify the denosing result, and the denosing result is evaluated by comparing the predicted root mean square error (RMSE) before and after denosing. Comparing the prediction results of the two groups of experiments, it is not difficult to find that the predicted RMSE after denosing is 0.00055, which is two orders of magnitude lower than the predicted RMS error before denosing (0.0125).