A method of predicting for trajectory of hypersonic gliding targets based on Bayesian inference
In order to solve the current issue that it's difficult to predict the trajectories of a hypersonic gliding reentry vehicle(HGRV)due to its strong maneuverability and flexibility,a trajectory prediction method of the HGRV based on Bayesian inference is proposed.The method is based on the information that the HGRV is going to attack a place and the battlefield situation,designing the intention cost function to quantify its intention.Adopting the Bayesian inference to iteratively deduce the maneuvering mode and motion state of the HGRV,and finally using the Monte Carlo sequential filtering method to compute the target's state distribution and predicting its trajectory.Simulation results show that the proposed method can effectively predict the trajectory of the HGRV and provide the probability of each target being attacked when there are multiple targets,which can give a reference to the defense to make decisions.
hypersonic vehicletrajectory predictionBayesian theoryMarkov processMonte Carlo sequential filteringno-fly zone
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维普
