Tracking algorithm of powered phase of multi-stage ballistic missile based on improved adaptive "current" statistical model

This paper is devoted to an improved adaptive "current" statistical(CS) model, aiming to improve the accuracy and robustness of tracking the powered phase of multi-stage ballistic missiles under unknown ballistic parameters. By introducing the Jerk model idea and incorporating the Jerk into the calculation of acceleration variance, the target acceleration variance in the model has been improved, enhancing the tracking ability of the model for weak maneuvering targets. Furthermore, by means of the target maneuvering detection function, the adaptive adjustment of the maneuver frequency in the model has been achieved, which improves the ability to combat sudden changes of target maneuvering. Simulation results demonstrate that the present model is able to stably track the powered phase state of multi-stage ballistic missile and precisely estimate the shutdown point states, exhibiting higher tracking accuracy and stronger robustness comparing with the conventional CS model and other adaptive CS models.