## 1 Introduction
### Motivations and Contributions  
To comprehensively address the existing lacunae in the literature, the present paper elucidates a pioneering model tailored for the meticulous selection of central frequencies during adversarial interactions between UAVs and jammers within the realm of A2G networks. In a marked departure from conventional studies, our approach harnesses the power of the Stackelberg game framework, thereby enabling the UAV to exhibit an adaptive spectral response when confronted with dynamic jamming onslaughts. Through a meticulous transformation of this game into a sophisticated linear programming paradigm, we are able to ascertain optimal mixed equilibrium strategies that boast of polynomial time complexity. The methodology we advocate for not only showcases an elevated performance when juxtaposed with traditional paradigms like FHSS and RS but also excels in terms of communication payoff and robust stability. This superiority is further underscored through rigorous analytical evaluations and simulation-driven validations. The salient innovations of our study are delineated as follows:  
(1) This study is at the forefront of revolutionizing central frequency selection optimization within Air-to-Ground (A2G) networks during adversarial UAV-jammer interactions. Departing significantly from conventional approaches, we harness the power of a Stackelberg game framework to empower UAVs with the ability to dynamically adapt their spectral responses. This innovative approach is strategically designed to effectively thwart dynamic jamming attacks and enhance the robustness of A2G communication networks;  
(2) Our approach strategically utilizes the dual-matrix game method to effectively convert the intricate Stackelberg game into a more tractable linear programming problem. This strategic transformation plays a pivotal role in mitigating the computational complexities that are inherently embedded within the original game formulation. Through this methodological adjustment, we streamline the analytical process, rendering it more accessible and facilitating expedient decision-making, thus significantly contributing to the overarching objective of our study;  
(3) In pursuit of our primary objective, we introduce an advanced algorithmic solution tailored to this linear programming problem. This approach has been rigorously validated and proven to deliver optimal mixed strategies efficiently within polynomial time. This remarkable achievement represents a substantial step forward, as it equips UAVs with the most advantageous mixed strategies, aligning with the core mission of our research--to enhance their operational effectiveness.  
The subsequent structure of this paper is meticulously delineated as follows. In Section 2, we delve into a detailed exposition of both the system and communication models pertinent to UAVs. Section 3 is dedicated to the elucidation of the Bimatrix Stackelberg Game model, coupled with a discussion on the optimization objectives and the formulation of the optimal mixed strategy. Section 4 furnishes the reader with empirical numerical results, shedding light on the practical implications of our proposed methodologies. Finally, Section 5 offers a holistic recapitulation of the entire discourse, encapsulating the key takeaways and insights.