Research On Boost Phase Trajectory Estimation Algorithm For The Space Based Infrared System Detection

With long range,high precision,fast speed and great power,ballistic missiles have become the essential strategic deterrent weapons in modern war.Therefore,ballistic missiles early warning and the corresponding systems construction have become strategic projects of the powerful military countries in the world.The space based ballistic missile early warning system is deployed in outer space and is less affected by the earth curvature.It has the characteristics of long warning time,precise warning information,wide coverage,and strong anti-interference.It is the key means of strategic early warning,and its typical representative is the Space Based Infrared System(SBIRS).At present,the research on boost phase trajectory estimation for the SBIRS detection mostly focus on the boost phase trajectory estimation which use two satellites detection data and the boost phase trajectory estimation which use single satellite detection data.The Extended Kalman Filtering algorithm and the Unscented Kalman Filtering(UKF)algorithm are commonly used in boost phase trajectory estimation.And most ballistic missile motion models adopt polynomial models such as the Constant Acceleration model and the Current Statistic(CS)model.The boost phase trajectory estimation performance isn’t high enough to meet the requirements for effective defense against incoming ballistic missiles.Therefore,focusing on how to improve the boost phase trajectory estimation performance using the SBIRS’s detection data,this thesis conducts research from the aspects of designing a nonlinear filter algorithm,establishing a precise motion model and introducing more satellite’s detection data.The specific contents are as follows:1.Aiming at designing a nonlinear filtering algorithm to improve the performance of the boost phase trajectory estimation,a boost phase trajectory estimation algorithm based on the CSCKF is proposed.The proposed algorithm introduces the Cubature Kalman Filtering(CKF)into the boost phase trajectory estimation based on the CS model.Combined with the characteristics of the CS model,the proposed algorithm is improved afterwards.The simulation results show that,under the condition that the estimation error is equivalent,compared with the CS-UKF based boost phase trajectory estimation algorithm,the CS-CKF based boost phase trajectory estimation algorithm requires approximately 7.9% shorter time;Compared with the CS-CKF based boost phase trajectory estimation algorithm,the required time of the simplified CS-CKF boost phase trajectory estimation algorithm is reduced by 33%.2.Aiming at establishing a precise motion model to improve the boost phase trajectory estimation performance,a boost phase trajectory estimation algorithm based on the incomplete thrust acceleration template is proposed.The incomplete thrust acceleration template is derived by ballistic missile’s finite prior information,the thrust direction angles are expanded to the target’s state components,A precise parameterized dynamic model is established by using the acceleration template.The boost phase trajectory estimation filtering algorithm adopts the CKF.According to the characteristic that the early turning angle of a ballistic missile in boost phase is very small,the initial thrust direction is estimated by the geocentric direction of the ballistic missile’s initial position,an adaptive process noise matrix is designed by using the first-order Markov process to describe the thrust direction angles.Simulation results show that,compared with the traditional algorithm based on the CS model,the estimation error of the proposed algorithm is significantly reduced and the filter stability is greatly enhanced.3.Aiming at introducing more satellite’s detection data to improve the boost phase trajectory estimation performance,a boost phase trajectory estimation algorithm based on the three satellites detection data fusion is proposed.The professional Satellite Toolkit software is used to analyze the SBIRS’s coverage capbility of over three satellites to a certain area,according to whether we have limited prior information about the missile,the proposed algorithm adopts the CS model or the model based on the incomplete thrust acceleration template respectively to establish the ballistic missile’s motion model,the Centralized Structure is used for data fusion,and the boost phase trajectory estimation filtering algorithm adopts the CKF.The simulation results show that whether the ballistic missile’s motion model adopts the CS model or the model based on the incomplete thrust acceleration template,compared with two satellites detection boost phase trajectory estimation algorithms,the estimation error of three satellites detection boost phase trajectory estimation algorithms are all significantly reduced.4.In order to visually show the boost phase trajectory estimation algorithms for the SBIRS detection,we developed a simulation system.Non-linear filtering algorithms,the CS model,the model based on the incomplete thrust acceleration template,the boost phase trajectory estimation algorithms based on two satellites detection,and the boost phase trajectory estimation algorithms based on three satellites detection are all integrated and implemented in the developed simulation system.