Research On Clutter Suppression Based On Sea Clutter Chaotic Characteristics

Sea clutter refers to the backscattered echo of the sea surface under radar illumination,which has a significant impact on the detection performance of targets such as ships in the ocean background.The complex and variable sea clutter signal has always been the main factor affecting the performance of the radar,because the existence of sea clutter will cause relatively large interference for radar detection of sea surface targets and tracking performance.In a large number of studies on sea clutter suppression,traditional methods often use statistical models to model the suppression of sea clutter.Commonly used models have lognormal distribution,k distribution and so on.The traditional method only studies the sea clutter from a statistical point of view,and can not accurately reveal the inherent physical mechanism and variation characteristics of sea clutter.Therefore,the fitting effect is not ideal and has limitations.With the establishment and development of nonlinear theory,nonlinear methods such as chaos provide new research ideas and methods for the suppression of sea clutter.Firstly,this paper studies the amplitude statistical characteristics of sea clutter,and the influence of the selection of parameters in the Rayleigh distribution,k distribution and other models on the model.And based on the IPIX radar data for amplitude fitting,it is better to analyze which model the sea clutter has.Secondly,based on the measured radar data,the chaotic dynamic characteristics of sea clutter are analyzed and verified.According to the Takens embedding theorem,the embedded delay time of the important parameters in the phase space reconstruction process is calculated by autocorrelation method and mutual information method respectively.The Cao method is used to calculate the embedding dimension.Because the finite correlation dimension and the positive maximum Lyapunov exponent are important basis for judging the system as a chaotic system,the two parameters are calculated by the GP method and the Wolf method respectively,and the chaotic characteristics of the sea clutter are further verified.the adaptive RBF fuzzy neural network and the improved adaptive learning algorithm are used to construct the chaotic dynamic system of sea clutter.Training prediction based on IPIX radar data.The simulation results show that the suppression of the clutter can be completed by prediction,and the target can be detected accurately.Finally,the sea clutter characteristic analysis platform is realized by using the GUI function of Matlab.The platform is divided into two modules:clutter statistical characteristics analysis and chaotic characteristic analysis,which have better human-computer interaction functions.The experimental results show that it is difficult to use a model to describe the amplitude characteristics of sea clutter.It is feasible to use the chaos theory and neural network technology to suppress sea clutter.And compared to other models,The method used in this paper and the improved adaptive learning algorithm have better prediction and cancellation performance.,which can effectively suppress clutter and improve the detection performance of weak targets.