Detection Method of Sea Surface Small Target Based on Improved Isolation Forest
To address the problem of radar small target detection under sea clutter conditions and the issue that the isolation forest(iForest)algorithm does not fully utilize radar echo signal features when dealing with high-dimension-al data,a method for weak target detection based on improved multi-feature joint isolation forest is proposed.This meth-od constructs a rich high-dimensional feature matrix by analyzing the characteristics of actual sea clutter data in time do-main,frequency domain and time-frequency domain.The principal component analysis is integrated into the isolation forest algorithm for data dimensionality reduction,introducing an average correlation-based dual-parameter criterion for dimensionality reduction to balance the correlation between the principal components and the original features.The simu-lation results demonstrate that the proposed method effectively enhances the detection performance of radar weak target under sea clutter conditions across different sea states and polarization modes,while maintaining a high detection proba-bility under low false alarm rates.
万方数据
维普
