To address the need for high-precision modeling in digital twin battlefields, this study proposes a six-degree-of-freedom digital twin model of a fixed-wing aircraft. The model adopts a modular and component-based architecture, enabling separate modeling of key components such as the fuselage and wings to enhance modeling granularity and flexibility. An improved Euler method is applied to increase the accuracy of dynamic simulation. Environmental response mechanisms—including standard atmosphere, icing, and rainfall models—are incorporated to dynamically adjust the aircraft’s characteristics under complex conditions. A genetic algorithm is employed to optimize the PID controller, enabling adaptive tuning with limited parameters. The proposed approach is innovative in its integration of fine-grained modeling with complex environmental responses, effectively addressing the limitations of traditional models in terms of low granularity and insufficient environmental representation. Simulation results demonstrate that the model exhibits strong stability and responsiveness, offering reliable support for digital twin modeling of battlefield equipment.