Analysis of detecting target in sea clutter using decoupled echo state network

This letter use echo state network (ESN) and three decoupled echo state network (DESN) to predict the sea clutter time series and detect target embedded in sea clutter. The performance of predicting and detecting using these methods is compared. A set of time series from IPIX radar data is tested. Numerical experiments reveal that DESN with maximum available information (DESN+MaxInfo) and DESN with reservoir prediction (DESN+RP) show higher prediction precision in pure sea clutter data. ESN has the better effect for detecting target in sea clutter.