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In this paper, we present a framework for tracking a moving target in urban environments using UAVs in cooperation with UGVs. The framework takes into account occlusions between the sensor and the target. The target state is modeled using the dynamic occupancy grid and the target motion model is built using a second-order Markov chain. Based on the target occupancy grid, we design the path planning algorithm to maneuver the UAV and the UGV to configurations where they can detect the target with high probability. Simulation results show the framework is successful in solving the target tracking problem in urban environments. We also build an indoor hardware platform and successfully implement preliminary tracking algorithms on the platform. Results show the platform can be further used to test more advanced tracking algorithms like the proposed tracking framework.