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This research effort focuses on determining the optimal flight path required to put a micro air vehicle's (MAVs) fixed sensor on a target in the presence of a constant wind. Autonomous flight is quickly becoming the future of air power and over the past several years, the size and weight of autonomous vehicles has decreased dramatically. As these vehicles were implemented into the field, it was quickly discovered that their flight paths are severely altered by wind. However, since the size of the vehicle does not allow for a gimbaled camera, only a slight perturbation to the attitude of the vehicle will cause the sensor footprint to be displaced dramatically. Therefore, the goal of this research was to use dynamic optimization techniques to determine the optimal flight path to place a MAV's sensor footprint on a target when operating in wind for three different scenarios. The first scenario considered the minimum time path given an initial position and heading and a final position and heading. The second scenario minimized the error between the MAV's ground track and a straight line to the target in order to force a desired path on the vehicle. The final scenario utilized both a forward mounted sensor as well as a side mounted sensor to optimize the time the target is continually in view of the sensor footprint. Each of these scenarios has been captured in simulated plots that depict varying wind angles, wind speeds, and initial and final heading angles. These optimal flight paths provide a benchmark that will validate the quality of future closed-loop wind compensation control systems.
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