Small Target Detection Method On Sea Surface Under Complex And Changing Sea Clutter Backgroun

The detection of small targets on the sea surface under the background of complex and changeable sea clutter is very important for ocean monitoring and national security.The complex and changeable sea surface environment seriously interferes with radar detection.Small targets on the sea surface have small radar reflection cross-sections and weak echo signals,which are often buried in sea clutter,making detection difficult.The detection of small targets on the sea surface under the background of sea clutter has always been a hot and difficult point in the field of radar signal processing.It has important theoretical significance and application value to study the characteristics of sea clutter and improve the detection rate.This paper studies the sea surface small target detection method under the complex and changeable sea clutter background,analyzes the characteristic difference between the sea clutter and the target echo,and proposes a sea surface small target detection method based on fine compound multi-scale scatter entropy and XGBoost and optimizes it based on genetic algorithm.The multi-feature sea surface small target detection method of sparse Bayesian extreme learning machine,according to the chaotic characteristics of sea clutter,establishes the sea clutter prediction model,realizes the sea surface small target detection,and provides the effective detection of sea surface small target under the background of sea clutter.theoretical approach.The specific research is as follows:(1)Study the entropy characteristics of sea clutter,and propose a small target detection method on the sea surface based on RCMDE-XGBoost.Variational mode decomposition is used to denoise and preprocess the complex and changeable sea clutter signals,the multi-scale features of the target are extracted through RCMDE,and input into the XGBoost network for feature classification.Through model training,small target detection on the sea surface is realized.The experimental results show that the detection rate of small targets on the sea surface based on RCMDE-XGBoost has reached 93.33%,92.38%,and 95% in #54,#311,and#320 sea situation HV polarization modes,respectively.This method can effectively improve complex Small object detection performance in variable sea clutter background.(2)Study the time-domain statistical characteristics of sea clutter,Alpha stable distribution,and multi-fractal characteristics,extract multi-dimensional features to construct feature vectors,and propose a multi-feature sea surface small target detection method based on GA-SBELM.Use GA-optimized SBELM for feature classification to realize small target detection on the sea surface.The experimental results prove that the detection rate of the multi-feature sea surface small target detection method based on GA-SBELM has reached 98.29%,92.46%,and 97.22% in #54,#311,and #320 sea situation HH polarization modes,respectively.Detection performance.(3)Study the chaotic characteristics of sea clutter,and propose a small target detection method on the sea surface based on the sparrow search algorithm to optimize the support vector machine.Using SSA to optimize SVM parameters improves the accuracy of prediction,reduces the detection threshold,and improves the detection rate.The experimental results show that this method can effectively realize the detection of small targets on the sea surface under the background of sea clutter.