Knowledge-Aided Sea Clutter Suppression Based on Echo State Network

Sea clutter suppression is critical in the detection of slow and small target. This paper studies the knowledge-aided sea clutter suppression based on echo state network (ESN). Aiming at the problem that the sea clutter suppression based on time series by ESN has poor suppression effect under the condition of high sea state and low signal-to-clutter ratio (SCR), We propose the knowledge-aided sea clutter suppression methods based on frequency spectrum and power spectrum by ESN. Sea clutter suppression is achieved by learning the sea clutter characteristics under the prior knowledge through ESN. We use the measured datasets of Ice Multiparameter Imaging X-Band (IPIX) radar for experimental verification, and the results show that the proposed methods can effectively suppress the sea clutter in different sea states and even detect the target with lower SCR.