The Prediction Model of IPIX Radar Sea Clutter Based on SSA-ELM Neural Network

Abstract

The prerequisite for improving radar detection capability is to reduction of sea clutter from interfering with the target, and the accurate prediction of sea clutter is an essential prerequisite for effective suppression. To achieve an accurate prediction of sea clutter, a model for sea clutter prediction combination of the salp’s swarm algorithm, prediction using extreme learning machine after performing parameter search, which improves the prediction performance of ELM and backpropagation (BP) neural network. The convergence speed and accuracy are improved, and the overall prediction The IPIX radar sea clutter prediction reaches an accuracy of more than 99% and the prediction results of this model are better than that when only using ELM or BP neural network prediction.