Optimal UAV Path Planning with Dynamic No-Fly-Zones for Target Geolocation Using Line-of-Bearing Measurements and Kalman Filtering
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Abstract
An optimal trajectory generation algorithm is needed for a Tactical Off-Board Sensing (TOBS) UAV to maximize the utility of its endurance while providing actionable target coordinates to other assets. A method of path optimization was developed to geolocate a stationary target using Line-of-Bearing measurements and to reach a prescribed orbit about the target in minimum time. Dynamic No-Fly-Zones (NFZ) were enforced, and different winds and initial conditions were simulated. A bootstrapping method was developed to approach the true minimum final time solution by iteratively minimizing the target covariance at a specified time step. A Kalman filter estimated the target position to a 6 meter CEP 90 requirement. Real-world scenarios were simulated for a candidate TOBS airframe and optimized to determine mission performance, trajectory characteristics, and to provide recommendations for the TOBS program. Simulations showed targeting time decreases of up to 19 dependent on wind conditions, and by up to 10 dependent on NFZ-relative launch positioning. Targeting requirements were met during all deviations from target orbit.