Abstract
In this paper, we present an optimal sensor management technique for an Unmanned Aerial Vehicle (UAV) to autonomously geo-localize multiple mobile ground targets. The target states are continuously estimated using target locations asynchronously captured by a gimbaled camera with a limited field of view and processed with a set of Extended Kalman Filters (EKFs). The technique incorporates a Dynamic Weighted Graph (DWG) method to first group estimated targets and then determine regions with high target densities. A Model Predictive Control (MPC) method is used to compute a camera pose that minimizes the overall uncertainty of the target state estimates. The validity of the proposed technique is demonstrated using simulation results.
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