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In the radar data processing, in order to better suppress sea clutter, sea clutter prediction is necessary. Sea clutter has chaotic features, and support vector machine algorithm can effectively carry out regression prediction of chaotic sequences, this paper proposes an improved support vector machine regression sea clutter sequence prediction algorithm. The paper gives the algorithm framework, using a mutual information method and improved pseudo-point method to extract neighboring sea clutter chaotic time delay and embedding dimension, using phase space reconstruction to strike SVM training sample, applying improved PSO algorithm to optimize kernel function parameter and penalty coefficient of SVM and simulate a prediction model. Simulation results show that:regression model to predict sea clutter is feasible and PSO-SVM method can further improve the prediction of sea clutter prediction accuracy.