Real Time Angle Of Attack Estimation For The Hycube Flight Vehicle In Gps-Denied Re-Entry

Abstract

With global interests in the study of hypersonic flow, large research efforts have gone towards collecting statistically significant amounts of high speed flow data at low costs. CubeSats are proving to be an economical testing platform for a variety of scientific experiments, where valuable hypersonic data can be collected and relayed upon re-entry to Earth. However, due to the budget, volume, and power constraints of CubeSats, many of the on-board sensors, including inertial measurement units (IMUS), have decreased accuracy. For purposeful data collection to occur, the sensors on-board typically work in conjunction with robust synthetic air data algorithms. To back out useful data on the vehicle's response during re-entry, the angle of attack of the vehicle must be estimated with one of such algorithms. This work proposes using an Extended Kalman Filter (EKF) which fuses an attitude determination algorithm with low-grade IMU angular rates and measurements of Earth's magnetic field. But in the case of re-entry, the vehicle will become deprived of Global Positioning System (GPS) data, which is required to obtain estimates of the Earth's magnetic field that work in conjunction with magnetometer magnetic field measurements. Thus, after developing the EKF framework, this work will perform a trade study to analyze ways in which Earth's magnetic field can still be a viable method to aid low-grade IMU attitude estimates. The trade study environment is modeled after the Hypersonic Configurable Unit Ballistic Experiment (HyCUBE), a project in development at the University of Minnesota that is leveraging the CubeSat form factors to collect valuable hypersonic flow data upon re-entry. Future work and improvements to the EKF, as well as the impact of this work will then be discussed.