Optimal Sensing for Tracking Task by Heterogeneous Multi-UAV Systems

A heterogeneous sensing multiunmanned aerial vehicle (UAV) system is developed to track a moving target undergoing unknown motion. Using heterogeneous sensors for tracking can increase robustness and reduce costs. However, the formation configuration of the multi-UAV system needs to be designed to ensure the best estimation performance. A metric based on the Fisher information matrix is used to determine the best formation configuration since the state covariance matrix was proven to be lower bounded by the Cramer-Rao lower bound. In other words, the determinant value of the Fisher information matrix is designed to be the cost function, and limitation of the field of view (FOV), limitation of the tracking distance, and avoiding inter-UAV collisions are considered as constraints. Finally, the generated optimal formation configuration is converted to the relative position for the distributed controller of the UAVs to achieve tracking. Controllers for UAVs are designed to ensure that tracking of the target is achieved in the optimal configuration with the constraints satisfied. In addition to performing the theoretical analysis, experiments and simulations were conducted to verify the efficacy of the developed heterogeneous sensing system.