A New Adaptive Tracking Algorithm for Near-Space Hypersonic Target
PROGRESS IN ELECTROMAGNETICS RESEARCH M(2018)
Abstract
Because of the maneuvering of hypersonic target, the tracking of near space hypersonic targets is difficult. In this paper, a new adaptive tracking algorithm based on an aerodynamic model and improved square root cubature Kalman filter is proposed. The adaptive piecewise constant jerk model gives the acceleration recursive process based on the dynamic model. Considering the nonlinear characteristic of both the target state model and the observation model, the improved square-root cubature Kalman filter is applied to estimate the target state. The simulation results under different maneuvers conditions indicate that the proposed method has a higher degree of accuracy than the original aerodynamic model. The research provides a feasible solution to the further improvement of the real time tracking accuracy of near space hypersonic targets.
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Key words
Deep Learning,Earth Rotation Monitoring,Nonlinear Electrodynamics,Hyperspectral Imaging,Ground Motions
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