Efficient Joint Deployment of Multi-UAVs for Target Tracking

Target tracking plays an important role in many real-world applications, such as in vegetation protection, disaster rescue, wildlife observation, etc. Multiple unmanned aerial vehicles (multi-UAVs) can provide effective services for target tracking through efficient joint deployment satisfying the system constraints. The constraints include the energy and no-fly zone constraint of each UAV, the communication distance and safe distance among multi-UAVs, the number of UAVs. As there exists no ready-made model that considers all the above constraints, meanwhile, the energy and no-fly zone restrict the deployment of multi-UAVs for target tracking. In this paper, we propose a model which considers no-fly zone and the energy constraint simultaneously for the joint deployment of multi-UAVs. The objective function is defined as minimizing the distance of each UAV and the threats of target so that it can deploy multi-UAVs reasonably. Second, we propose an improved Nondominated Sort Genetic Algorithm II (NSGAII) with new encoding and decoding mechanisms and the no-fly zone avoidance strategy which can improve the searching performance of joint deployment of multi-UAVs. Finally, we design a set of experiments and the experimental results demonstrate that our proposed algorithm can deploy multi-UAVs for target tracking efficiently compared with the state-of-the-arts methods.