Satellite Attitude Determination Using Magnetometer Data Only

Abstract

On March 8, 2007, the U.S. Air Force Academy launched FalconSAT 3, a complex small satellite with three plasma-researching payloads supporting Department of Defense funded science missions. This is the first three-axis stabilized satellite designed, tested, and built by cadets. FalconSAT 3 is equipped with two types of satellite attitude sensors: magnetometers and sun sensors. However, a software issue inhibits the use of sun sensors, so development of a new method of attitude determination was required. The three-axis magnetometers would need to provide the means to accurately depict the spacecraft's orientation at any given time. Because of the ambiguity involved with using a single form of spacecraft attitude information, Extended Kalman Filtering became a viable solution that would combine insufficient data with a mathematical model of satellite motion to achieve accurate attitude estimation. First, a single-axis Kalman Filter was created for determining the yaw axis, assuming roll and pitch remain zero due to gravity-gradient stabilization. It was found that a constant gain filter can sufficiently provide pointing knowledge, depending on the user's needs. This yaw-estimator also initializes a starting point for a three-axis estimator. Generating a six-state, three-axis control Extended Kalman Filter for attitude determination became the primary focus of research because the FalconSAT 3 payloads require accurate attitude determination. Looking to the future, modification of this three-axis estimator accounts for a pitch wheel considered for FalconSAT 5, a satellite that the U.S. Air Force Academy proposes to launch in December 2009. These three Kalman Filters were developed in England at the Surrey Space Centre and were tested and tuned with magnetometer data of a Surrey Space Technology Limited (SSTL) satellite called UoSAT. Comparing the attitude estimation results to the truth model of UoSAT shows that the Extended Kalman Filters converge to within one degree of accuracy. This paper details the theory behind these Kalman Filters in addition to their tuning and results.

Implementation and Hardware-In-The-Loop Simulation of a Magnetic Detumbling and Pointing Control Based on Three-Axis Magnetometer Data

“…This result can be easily extended to case (a). It is worth to highlight that similar configurations produce a predictable attitude motion of the satellite which, in case of failure of the primary attitude determination devices, improving the survivability of the mission and allowing to implement magnetometer-only attitude estimation strategies [23][24][25][26][27][28][29][30][31].…”

Design and Numerical Validation of an Algorithm for the Detumbling and Angular Rate Determination of a CubeSat Using Only Three-Axis Magnetometer Data

“…A similar magnetometer-only deterministic algorithm was originally proposed by Oshman and Dellus [25], for a LEO satellite actuated by momentum wheels, and later improved by Psiaki and Oshman [26]. The angular rates are here determined calculating the orthogonal component ω ⊥ by means of an equation equivalent to (4)…”

“…The problem of magnetometer-only attitude determination has been extensively examined through the last thirty years, with relevant results obtained first by Natanson et al, for spacecraft rotating with constant angular rate and later extended to the case with no a priori knowledge of the spacecraft state with uses of a Kalman filter [1,2]. As reviewed by Hajiyev and Guler [3], several algorithms include a single-or multiple-step extended Kalman filter [4][5][6][7][8][9] or an unscented Kalman filter [10]. Other approaches are based on deterministic two vector methods [11][12][13] and are typically preferred when computational efficiency of the onboard computer is limited and lower measurement accuracy is acceptable.…”

A Magnetometer-Only Attitude Determination Strategy for Small Satellites: Design of the Algorithm and Hardware-in-the-Loop Testing

“…The most popular methods for three-axis magnetometer-only attitude determination are based on the Extended Kalman Filter (EKF) and can reach an accuracy below 5 • on attitude and 0.01 • /s on the angular rates [21][22][23]. Other solutions include the Unscented Kalman Filter (UKF) algorithm by Ma and Jiang [24], or the two-step EKF algorithm proposed by Searcy and Pernicka [25], which achieves accuracies of less than 1 • , but is effective only if the angular rates along at least one axis exceeds 0.1 • /s.…”