Abstract
Most satellites use an on-board attitude estimation system, based on available sensors. In the case of low-cost satellites, which are of increasing interest, it is usual to use magnetometers and Sun sensors. A Kalman filter is commonly recommended for the estimation, to simultaneously exploit the information from sensors and from a mathematical model of the satellite motion. It would be also convenient to adhere to a quaternion representation. This article focuses on some problems linked to this context. The state of the system should be represented in observable form. Singularities due to alignment of measured vectors cause estimation problems. Accommodation of the Kalman filter originates convergence difficulties. The article includes a new proposal that solves these problems, not needing changes in the Kalman filter algorithm. In addition, the article includes assessment of different errors, initialization values for the Kalman filter; and considers the influence of the magnetic dipole moment perturbation, showing how to handle it as part of the Kalman filter framework.
Highlights
Most satellites have an attitude determination and control system (ADCS) [1]
In the case considered in this article, the satellite attitude is a state vector to be estimated from the measurements obtained with a Sun sensor and a magnetometer
Let us advance that, if one uses a Kalman filter based on Equations (19) and (20) for angular velocity estimation, the result could be as depicted in Figure 2, which corresponds to the simulation velocity estimation, the result could be as depicted in Figure 2, which corresponds to the simulation of of a typical satellite behavior
Summary
Most satellites have an attitude determination and control system (ADCS) [1]. In a space telescope the target of ADCS would be to obtain an accurate and stable position pointing to a desired target in the sky. Somewhen ill conditioned problems can arise, causing the Kalman filter to During orbital motion, some ill conditioned problems arise, causing theisKalman filter to malfunction This is the main point addressed by this article,can in which a solution proposed. Quaternion Determination: The quaternion (q, σq) that describes the satellite orientation would be computed from measured vectors and calculated vectors It will be shown in this article that ill conditioned problems can appear. In [14] an inertial measurement unit (IMU) based on accelerometers was chosen; the article discusses observability issues and presents an extended Kalman filter (EKF) solution. In addition to the contributions on observability and overcoming ill conditioned situations, the article includes an assessment of the importance of several types of errors present in the ADCS
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