Even with recent advances in computing power the development of smaller Unmanned Aerial Vehicles (UAVs) and sophisticated sensor payloads with high data rates can still challenge on-board computer resources. In response to this challenge, gain scheduling is investigated as a means to reduce the computational burden associated with a nonlinear attitude estimator. The attitude/heading filter used to validate the gain scheduling approach is based on an Euler angle parameterization. Its process dynamics and measurement updates are provided by nonlinear rate kinematic equations and absolute attitude measurement updates, respectively. The gain scheduling approach is intended to be instrumentation independent for the attitude parameterization used.
Validation of the gain scheduling attitude/heading estimation filter utilized process dynamics driven by a low-cost Micro-Electromechanical System (MEMS) based Inertial Measurement Unit (IMU). Measurement updates are provided by an external machine-vision infrared tracking system. The gain scheduling approach should be applicable to other sensor types such as GPS, magnetometers, and other aides. Gain scheduling filter development has been tested using simulated trajectories and real data collected from a remote control helicopter own indoors and processed off-line.
University of Minnesota M.S. thesis. March 2012. Major: Aerospace engineering and mechanics. Advisor: Dr. Demoz Gebre-Egziabher. 1 computer file (PDF); xiii, 79 pages, appendices A-C.
Horkheimer, Donald Patrick.
Gain scheduling of an extended Kalman Filter for use in an attitude/heading estimation system..
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