A new adaptive estimation method of spacecraft thermal mathematical model with an ensemble Kalman filter

An adaptive estimation method of spacecraft thermal mathematical model is presented. The method is based on the ensemble Kalman filter, which can effectively handle the nonlinearities contained in the thermal model. The state space equations of the thermal mathematical model is derived, where both temperature and uncertain thermal characteristic parameters are considered as the state variables. In the method, the thermal characteristic parameters are automatically estimated as the outputs of the filtered state variables, whereas, in the usual thermal model correlation, they are manually identified by experienced engineers using trial-and-error approach. A numerical experiment of a simple small satellite is provided to verify the effectiveness of the presented method.

► We present an adaptive estimation method of spacecraft thermal mathematical model.
► We utilize the ensemble Kalman filtering (EnKF) technique for nonlinear systems.
► Both spacecraft temperature and uncertain thermal parameters are estimated.
► A numerical experiment of a simple small satellite is provided.
► A self-tuning of filter setting is performed by using the steepest descent method.