The Balloon Experimental Twin Telescope for Infrared Interferometry (BETTII) is an 8-meter baseline far-infrared interferometer designed to fly on a high altitude balloon. BETTII uses a double-Fourier Michelson interferometer to simultaneously obtain spatial and spectral information on science targets; the long baseline provides subarcsecond angular resolution, a capability unmatched by any other far-infrared facilities. BETTII had its first successful engineering flight in June 2017. The pointing loop on BETTII is based on an Extended Kalman Filter, which uses different sensors and actuators to keep the telescope pointed at the desired target star. In order to achieve high precision pointing, we use an embedded Field-programmable gate array (FPGA) that combines the gyroscope and star cameras information to generate a pointing solution every 10 milliseconds. The BETTII control system serves a critical function in making interferometric observations possible. This paper discusses the design and implementation of the BETTII control system and presents engineering data of the attitude control system from our pre-flight tests at the Columbia Scientific Balloon Facility (CSBF) and data from our first 12-hour flight from Palestine, TX. This includes pointing performance of the Kalman Filter estimator in the RA, DEC and ROLL Equatorial Coordinate System as well as the payload’s attitude behavior when switching between the different modes we implemented: Safe, Brake, Slew, Track and Acquire. These modes are part of the procedure to point the telescope to a desired target. We discuss the performance of the payload’s control system in each of these modes and present data showing how the azimuth actuators follow the position and velocity profiles calculated by the flight computers.
Attitude determination is one of the most important subsystems in spacecraft, satellite, or scientific balloon mission s, since it can be combined with actuators to provide rate stabilization and pointing accuracy for payloads. In this paper, a low-cost attitude determination system with a precision in the order of arc-seconds that uses low-cost commercial sensors is presented including a set of uncorrelated MEMS gyroscopes, two clinometers, and a magnetometer in a hierarchical manner. The faster and less precise sensors are updated by the slower, but more precise ones through an Extended Kalman Filter (EKF)-based data fusion algorithm. A revision of the EKF algorithm fundamentals and its implementation to the current application, are presented along with an analysis of sensors noise. Finally, the results from the data fusion algorithm implementation are discussed in detail.
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