Weak Target Detection Based On The Chaotic Characteristics Of Sea Clutter

With the development of radar technology,target detection in sea clutter becomes an important part of radar signal processing.Sea clutter generally refers to the radar backscatter from the ocean surface,which often results in serious interference to the detection performance of radar targets.In the detection of weak targets in sea clutter,the traditional method is based on the statistical characteristics of sea clutter.But the statistical characteristics cannot well reflect the intrinsic dynamics characteristics of sea clutter,so the detection effect is not ideal.With the emergence of chaotic characteristics of sea clutter,it provides a new method for the detection of weak targets on the sea surface.Therefore,by analyzing the chaotic characteristics of sea clutter,This paper researched an RBF-based self-adaptive fuzzy neural network for target detection.The main research contents are divided into four parts:The first part consists of chapter 1 and 2:In this part,this section first recounts the significance of the research of sea clutter,and introduces the research statue of sea clutter from the statistical theory,fractal theory and chaos theory.And then describes the chaos theory and several common models of chaotic attractor.Finally,the source and acquisition of IPIX radar sea clutter are described.The second part consists of chapter 3:In this part,the chaotic dynamic characteristics of radar sea clutter data are verified.The famous Takens theorem is introduced and the phase space reconstruction of sea clutter time series is discussed.The key problem of phase space reconstruction is analyzed,which is the calculation of delay time and embedding dimension.In this paper,the autocorrelation function method and mutual information method are used to calculate the delay time.False nearest neighbors method and Cao method are used to calculate the embedding dimension.GP method and small data method are used to calculate the correlation dimension and the largest Lyapunov exponent respectively,according to the finite correlation dimension and the positive Lyapunov exponent,so as to verify the chaotic characteristics of sea clutter.The third part consists of chapter 4:This section uses the chaotic characteristics of sea clutter,and studies the method of RBF-based self-adaptive fuzzy neural network of weak target detection based on chaotic background.A one-step prediction model is established to detect the weak target from the prediction error submerged in chaos in the background,using Lorenz system and the measured IPIX radar data as chaotic background was researched.The simulation results show that this method can effectively detect signal in chaotic background signal.Finally,compared with the RBF neural network prediction,the adaptive fuzzy neural inference system has better prediction effect,so it can achieve better detection of the target.The fourth part consists of chapter 5:In this part,according to the idea of software modularization,the above algorithms are integrated in the Matlab software,and a good platform for the detection of chaotic characteristics of sea clutter is designed.The platform consists of three modules:phase space reconstruction,chaos identification and target detection.