Smart sensor data processing for aerospace applications in education illustrated by small satellite platform demonstrator

This article describes a tasks for undergraduate students from the area of signal processing that is often used in aerospace for data fusion of different kinds of sensors onboard of an airplane or a spacecraft. It includes a Kalman filter merging angular rates, accelerations and vector of the magnetic field. These topics are illustrated on a remotely controlled educational platform and its internal Inertial Measurement Unit. The article describes a set of sequential topics that introduces students with Attitude Heading and Reference System data processing on a remotely controlled platform that contains all necessary sensors. The hands-on experiments with the remotely controlled platform presented in this article takes advantages of the existing technology and shifts the currently used educational approach to the more interactive level. We mainly describe an algorithm to calculate position angles from raw sensor data which is used within Attitude Heading and Reference Systems and we propose a new arrangement of the AHRS unit which uses self-calibrating magnetometer and the Pressure Reference System for pitch and roll angles measurements to remove influence of accelerations generated during the flight.