Satellite Inertia Parameters Estimation Based on Extended Kalman Filter

Abstract

The moment of inertia parameters play a critical role in assuring the spacecraft mission throughout its lifetime. However, determination of the moment of inertia is a key challenge in operating satellites. During satellite mission, those parameters can change in orbit for many reasons such as sloshing, fuel consumption, etc. Therefore, the inertia matrix should be estimated in orbit to enhance the attitude estimation and control accuracy. This paper investigates the use of gyroscope to estimate the attitude rate and inertia matrix for low earth orbit satellite via extended Kalman filter. Simulation results show the effectiveness and advantages of the proposed algorithm in estimating these parameters without knowing the nominal inertia. The robustness of the proposed algorithm has been validated using the Monte-Carlo method. The obtained results demonstrate that the accuracy of the estimated inertia and angular velocity parameters is satisfactory for satellite with coarse accuracy mission requirements. The proposed method can be used for different types of satellites.

Automatic Balancing for Satellite Simulators with Mixed Mechanical and Magnetic Actuation

“…This latter was estimated, along with the inertia parameters, through off-line least-squares filtering of the angular velocity data sampled during free platform oscillations (step 2). Indeed, platform balancing is inherently related to inertia identification [15][16][17][18], with the latter usually required to complete the former.…”