Distributed Sea Clutter Denoising Algorithm Based on Variational Mode Decomposition

Abstract

In order to improve the detection accuracy of chaotic small signal prediction models under the background of sea clutter, a distributed sea clutter denoising algorithm is proposed, on the basis of variational modal decomposition (VMD). The sea clutter signal is decomposed into variational modal functions (VMF) with different center bandwidths by means of VMD. By analyzing the autocorrelation characteristics of the decomposed signal, we perform instantaneous half-period (IHP) and wavelet threshold denoising processing on the high-frequency and low-frequency components respectively, and regain the sea clutter signals. Based on LSSVM sea clutter prediction model, this research compares and analyzes the denoising effects of VMD. Experiment results show that, the RMSE after denoising is reduced by two orders of magnitude, approximating 0.00034, with an apparently better denoising effect, compared with the root mean square error (RMSE) of the prediction before denoising.