Tracking micro reentering USV with TDRS and ground stations using adaptive IMM method

In this paper, a tracking system with multi-sensors is presented, in which a sub-orbit USV (unmanned space vehicle) of wave-rider shape is tracked by a TDRS (Tracking and Data Relay Satellite) and ground stations. Because of high lift-drag ratio and maneuverability, the vehicle, once is used in reentering purpose, a complicated trajectory will be produced and cause big challenges for tracking facilities. Although TDRS has more coverage capability than ground stations, unlike tracking stations fixed on the ground, when its antenna tracks target, the platform it located on will do some attitude maneuver to balance the effects caused by the antenna´s moving. This will lead some errors in tracking the target and should be taken into account when processing the data. To solve these problems, a fusion strategy of improved IMM (Interacting Multiple Model) with different kinematics and measurement models is designed in this paper, which helps to process the trajectory data and estimate aerodynamic parameters of the vehicle. In the dynamic model, both trajectory parameters and aerodynamics parameters are calculated, the measurement models are either TDRS or ground tracking stations. Meanwhile, in the adaptive IMM algorithm, an adaptive method for calculating transition probabilities of time-varying transition model is designed. Also the Iterated Sigma Point Kalman Filter (ISPKF) is used helping make the system more robust and perform better. Simulation results show that the proposed algorithm performs well in tracking high lift-drag ration re-entering vehicle and estimating the aerodynamics parameters as well.