Study On Ground Target Location And Tracking Algorithm Based On Near Space Platform

Near space has great strategic value,in recent years,near space vehicle has quickly attracted the attention of many countries.The aerospace powers,represented by the United States,have carried out the research and development of near space vehicle.The development and application of near space vehicle technology will have a significant and profound influence on national security and human life and has become the world military competition of the new strategic high ground.As a key technology in the near space vehicle technology,ground target location and tracking making the near space vehicle obtain the target position and state quickly and accurately,is the basis and prerequisite to complete various tasks.This paper focuses on ground target location and tracking algorithm based on near space platform.The main work of this paper is as follows:(1)The research background and significance of target location and tracking based on near space vehicle are elaborated.Research status at home and abroad is summarized.The fundamental knowledge of passive location and tracking technology by single observer is inroduced.(2)The single station passive location method applied to the special height and environmental characteristics of near space is studied.Location and tracking model are established,including the state model and observation model,single positioning error are analyzed.Simulation experiments about the influence factors of single measurement error are conducted.(3)Aiming at the problem that the traditional tracking filter algorithm has low accuracy and poor stability,a new nonlinear filtering algorithm namely Cubature Kalman filter(CKF)is applied to the problem of single station passive location based on near space vehicle.The basic idea of CKF algorithm is based on spherical-radial cubature rule,using an even number of equally weighted cubature points to calculate the posterior probability density,and then realize the estimate of the state vector.The algorithm is easily achieved and does not need calculate the Jacobian matrix as well as set the appropriate parameters.Furthermore,the position and velocity information of target can get more quickly and accurately.(4)Aiming at the problem that CKF is not suitable for the non-gaussian noise,the CPF algorithm combining the CKF and PF algorithm is used in the problem of single station passive location based on near space vehicle.The basic idea of CPF algorithm is introducing CKF algorithm to the process of generating the importance density function in PF algorithm,retaining the advantage of PF algorithm which is suitable for non gaussian noise environment.What is more,the CKF is used to generate the importance density function with the new measurement information added making it closer to the posterior probability distribution of the system,therefore,state estimation is more accurate.The simulation results show that CPF algorithm can realize location and tracking for target more steadily,more rapidly and accurately in nonlinear and non-gaussian system.