Estimation of Pico-Satellite Attitude Dynamics and External Torques via Unscented Kalman Filter

Abstract

In this study, an Unscented Kalman Filter (UKF) algorithm is designed for estimating the attitude of a picosatellite and the in-orbit external disturbance torques. The estimation vector is formed by the satellite's attitude, angular rates, and the unknown constant components of the external disturbance torques acting on the satellite. The gravity gradient torque, residual magnetic moment, sun radiation pressure and aerodynamic drag are all included in the estimated external disturbance torque vector. The satellite has magnetometers and gyros onboard as the attitude sensors. Because of the inherent nonlinear dynamics and the nonlinear measurement model, the UKF, which is a nonlinear version of the Kalman Filter, is selected as the filter algorithm. Performance of the proposed algorithm is demonstrated via simulations for a cube pico-satellite and the results are analyzed for different scenarios.

Attitude filtering with uncertain process and measurement noise covariance using SVD‐aided adaptive UKF

“…The nonlinear measurements of reference directions can be used to create a Kalman filter for satellite attitude and rate estimates in traditional approaches. [1][2][3][4] The nonlinear models of the reference directions serve as the foundation for the measurement models in the filter. Therefore, nonlinear equations are used to link the data and states.…”

“…To estimate the attitude of the satellite, the simple concept is to compare the vectors measured in the body frame with the known vectors in the inertial (or any other reference) frame. 3,5 When employing the conventional attitude filtering methodology, it is possible to retrieve the initial values for the Kalman filter using a single-frame method. 6 In Reference 7, to conduct a cost-benefit analysis, various spacecraft attitude estimation and determination techniques are studied.…”

“…The quaternion's unit‐constraint is enforced by a dummy measurement of quaternion norms. Another traditional UKF is presented in Reference 2 for estimation of the attitude and external torques. That algorithm is designed based on the magnetometer and rate gyro measurements.…”

“…The measurements in the conventional attitude filter may reference the Earth's magnetic field vector or to any of the direction vectors to the Sun, star, etc. To estimate the attitude of the satellite, the simple concept is to compare the vectors measured in the body frame with the known vectors in the inertial (or any other reference) frame 3,5 . When employing the conventional attitude filtering methodology, it is possible to retrieve the initial values for the Kalman filter using a single‐frame method 6 .…”