Game-Based Strategy to Cooperative Localization with Input Constraints

The cooperative localization of multiple drones in space with a certain configuration to target enhances the acquisition of information and boosts situational awareness, presenting significant application prospects. Addressing the challenge of achieving high-precision cooperative localization for maneuver targets, this paper designs a Nash-based game cooperative localization strategy. Firstly, it establishes the cooperative localization scenario as a Stackelberg model and considers both localization accuracy and input constraints. Secondly, it theoretically derives the Nash equilibrium solution of the game model for multi-aircraft. Thirdly, an improved data-driven adaptive dynamic programming algorithm with independent actions is devised to solve the equilibrium solution. Finally, simulations verify that the proposed model and algorithm can achieve cooperative localization of maneuvering targets by multiple drones, meeting the requirements for localization accuracy. This provides a solution for the research of strategies in cooperative adversarial scenarios.