An active three-axis gimbal system is developed to allow small fixed wing Unmanned Aircraft Systems (UAS) platforms to estimate accurate position information by pointing at a target and also to track a known target location. Specific targets vary from a stationary point on the ground to aircraft in the national airspace. The payload developed to accomplish this at the University of North Dakota is the Surveillance by University of North Dakota Observational Gimbal (SUNDOG). This paper will focus on a novel, nonlinear closed form analytical algorithm developed to calculate the exact rotation angles for a three-axis gimbal system to point a digital imaging sensor at a target, as well as how to estimate accurate position of a target by using the pointing angles of a three-axis gimbal system. A kinematic analysis is done on a three-axis gimbal system to get the appropriate model of gimbal rotations in order to point at a certain location on the ground. The mathematical model includes an inertial coordinate system that has coordinates fixed to the Earth, a coordinate system that is body-fixed to the aircraft, and a third coordinate system that is fixed to the gimbal. Therefore, multiple three-dimensional transformations are required to accurately provide the necessary pointing angles to the gimbal system. The autonomous control system uses Global Positioning System (GPS), Inertial Measurement Unit (IMU), and other sensor data to estimate position and attitude during flight. Since the algorithm is entirely based on Inertial Measurement Unit (IMU) and Global Positioning System (GPS) device inputs, any error from these devices cause offset in the target location. Hence, an error analysis is carried out to find the offset distance and the operating range of the algorithm. The main advantage obtained in the three-axis gimbal system is that the orientation of the image will always be aligned in a specified direction for effective interpretation. The closed form expressions to the non-linear transformations provide simple solutions easily programmed without large computational expense. Experimental work will be carried out in a controlled environment and in flight testing to show the autonomous tracking ability of the gimbal system. Simulation and experimental data illustrating the effectiveness of the surveillance algorithms is presented.

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