Abstract
Attitude determination represents a fundamental task for spacecraft. Achieving this task on small satellites, and nanosatellites in particular, is further challenging, because the limited power and computational resources available on-board, together with the low development budget, set strict constraints on the selection of the sensors and the complexity of the algorithms. Attitude determination is obtained here from the only measurements of a three-axis magnetometer and a model of the Geomagnetic field, stored on the on-board computer. First, the angular rates are estimated and processed using a second-order low-pass Butterworth filter, then they are used as an input, along with Geomagnetic field data, to estimate the attitude matrix using an unsymmetrical TRIAD. The computational efficiency is enhanced by arranging complex matrix operations into a form of the Faddeev algorithm, which is implemented using systolic array architecture on the FPGA core of a CubeSat on-board computer. The performance and the robustness of the algorithm are evaluated by means of numerical analyses in MATLAB Simulink, showing pointing and angular rate accuracy below 10° and 0.2°/s. The algorithm implemented on FPGA is verified by Hardware-in-the-loop simulation, confirming the results from numerical analyses and efficiency.
Highlights
Mission operations often require the capability to orient the spacecraft in a specific direction.To perform these maneuvers, an adequately accurate knowledge of the spacecraft orientation in space, namely its attitude, is required, and this is the goal of attitude determination
We propose a simple attitude determination strategy suitable to be implemented on an FPGA-based On-Board Computer (OBC)
Can be implemented on FPGA by means of the Faddeev algorithm [34], using a single systolic array architecture. It means that the FPGA area dedicated to the systolic array can be used to calculate the results for any vector or matrix operation expressed in the form of Equation (5), taking advantage of parallel computing and reducing the usage on FPGA, increasing the efficiency of the algorithm [35,36,37]
Summary
Mission operations often require the capability to orient the spacecraft in a specific direction. Gyroless attitude determination methods are of interest as backup solutions for small satellite missions that do not require high pointing accuracy for basic operations [13] Such a solution can be effective when the above-mentioned measurement drift increases above a threshold level, in case of failure of the sensor and in the presence of an error in the algorithm which produces the interpretation of the signal. 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 Despite their rather high accuracy, the mentioned algorithms either require sophisticate models for vector estimation, are effective only under some specific attitude control, or include complex vector and matrix operations.
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