In this scientific initiation project, it is proposed to develop a low cost sensing system for a CubeSat. In estimating the attitude, orientation and position of the satellite it is intended to use gyroscopic sensors, accelerometers, magnetometers and a GPS receiver (Global Positioning System). The sensor data will be processed using filters, especially Kalman filters, in order to minimize the errors of each sensor in the composition of the final measurement. However, this project will use low-cost sensors, which generally means increased uncertainty and noise from the sensors. Therefore, robust estimators based on the Kalman filter will be employed to minimize these effects. Experimental results will be presented based on a comparative study between the performances of the estimators based on the Kalman filter and the robust Kalman filter.
News published in Agência FAPESP Newsletter about the scholarship: