Abstract: Reentry body transonic aerodynamic parameter online identification methods are researched, and an
augmented extended kalman filter is used as the online identification tools. Effect of the augmented extended kalman filter approach on joint state and parameter estimation is overall analyzed, and it is found that slowly varying parameters are well estimated,
but estimate values for fast varying parameters are largely divergent. To overcome this disadvantage, a new kind of strong tracking filter is introduced into the traditional augmented extended kalman filter, the simulation shows that strong tracking filter can effectively overcome the disadvantage of larger estimation error for general augmented extended kalman filter.

Key words: AuGmented extended kalman filter, StronG tracking filter, Online identification