UAV Swarm-Enabled Localization in Isolated Region: A Rigidity-Constrained Deployment Perspective
Qirui Liu, Rongke Liu, Zijie Wang, John Thompson
Abstract
In isolated regions, utilizing the unmanned aerial vehicle (UAV) as an aerial anchor node is a promising technique to enable location awareness of ground terminals (GTs). In this letter, considering a UAV swarm-enabled localization for a group of distributed GTs, we aim to minimize the maximum Cramer-Rao lower bound (CRLB) for position estimates with anchor uncertainty. Then, an efficient differential evolution (DE)-based method is proposed to find a sub-optimal solution. In particular, the rigidity of the UAV swarm is recognized as a critical constraint in the problem formulation to provide a unique swarm coordinate configuration and to maintain a prescribed flight formation. A gradient-based local optimization for rigidity is then proposed and embedded in the DE algorithm. Numerical results demonstrate that our proposed designs can reach better performance in localization accuracy while ensuring the rigidity of the UAV swarm, as compared with a random approach.