A simple suboptimal Kalman filter implementation for a gyro-corrected satellite attitude determination system

Abstract

This article presents a simple Kalman filter implementation for correcting gyro-determined satellite attitude estimates with attitude measurements made using external sensors such as sun sensors, magnetometers, star trackers, and so on. This article first generalizes a recently developed non-linear observer for the gyro-corrected attitude determination problem. By implementing the steady-state Kalman filter in the framework of this non-linear observer, a computationally simple filter is obtained with suboptimal steady-state performance. This is important for applications where computational power is limited, such as in micro-/nano-satellite applications. Additionally, in the absence of process and measurement noise, this implementation of the Kalman filter is globally stable. The resulting filter uses constant steady-state Kalman filter gains. It is demonstrated that close-to-optimal steady-state performance is obtained.