Research On Radar Detection,Tracking And Prediction Algorithm For The Boost-glide Hypersonic Vehicle

The near space boost-glide hypersonic flight technology is becoming more and more mature.This paper studies the dynamics modeling,detection technology,tracking and prediction technology of the near space boost-glide hypersonic vehicle.1.In reference to the establishment of long-range rocket flight dynamics model,the key work is to fit aerodynamic parameters of a boost glider,thus establishing a dynamic model of a boost glider under the launching system.This paper investigate and research the typical flight mode of boost-glide vehicle,including steady attack angle and equilibrium glide,then analysis the boost-glide vehicles' ballistic characteristics in typical flight modes,such as trajectory shape,velocity,range and height variation are presented.The influence of plasma on radar RCS of near space hypersonic vehicle is analyzed.Some common radar operational indexes are selected,and particle swarm optimization(PSO)is used to solve the problem of ground radar deployment optimization for hypersonic targets.2.The traditional tracking model,such as the Current Statistics model,is used to track the boost glide target.The maneuvering frequency and acceleration variance of the Current Statistics model have a great influence on the tracking accuracy.Blind selection can even cause filtering divergence,so an robust algorithm is used in Kalman filter to reduce the influence of model inaccuracy.The classical IMM algorithm of maneuvering target tracking field is selected to track the boost-glide target,in view of the shortcomings of IMM model in probability calculation,re design its model probability,mainly related to the modified model likelihood probability calculation.3.The tracking dynamics model is established,and the IMM is combined with nonlinear filtering algorithm to track the boost-glide target,Because of the large amount of computation,a nonlinear tracking method based on single model is established by improving the tracking dynamics model.The attack angle and roll angle of the two control variables are augmented into the state vector,when filtering,the state estimation and parameter estimation parallel computation can be used to establish the tracking dynamics model for the flight dynamics of the boost glider under different flight modes.Nonlinear filtering algorithm used in this paper is CKF,aiming at two problems when using the CKF: unknown statistical characteristics of process noise and probable measurement outliers,Sage-Husa noise estimator and Huber functions are used respectively for reference.4.Based on the tracking of this paper,three methods were used for trajectory forecast,which are the method based on the fitting of non conservative force,the method based on the fusion of multiple dynamic model prediction,the method based on the flight pattern recognition.