尾座式无人机共轴双旋翼的气动优化设计面临需要兼顾多飞行模式设计需求与旋翼间复杂气动干扰的技术挑战。针对该问题，构建了基于黏性涡粒子方法（VVPM）与格子涡（VIC）混合方法的高置信度气动模型，并针对旋翼气动优化需求设计了多重置信度贝叶斯优化策略，实现了计算资源与优化精度的平衡。以旋翼悬停功率与前飞功率为多优化目标，求解得到共轴双旋翼气动设计方案的帕累托最优解集。结合旋翼流场分析，悬停优化方案通过中段宽弦长与梯度扭转设计有效抑制桨尖涡发展与提升悬停效率，前飞优化方案采用内侧弦长递增及高梯度扭转设计可降低型阻功率与提升巡航效率，但会导致悬停桨尖涡过早卷起，降低悬停性能；折中优化方案通过平衡弦长梯度与扭转角配置，协同兼顾悬停与前飞性能，突破单一优化的局限。

The aerodynamic optimization design of coaxial rotor for tailsitter UAV faces challenges in balancing multiple flight modes and addressing complex aerodynamic interference between rotors. To address these challenges， this study establishes a high-fidelity aerodynamic model based on a hybrid Viscous Vortex Particle Method （VVPM） and Vortex-In-Cell （VIC） approach. A multi-fidelity Bayesian optimization strategy is designed to balance computational costs and accuracy for rotor aerodynamic performance. By treating rotor hover power and forward-flight power as dual optimization objectives， a Pareto optimal solution set for the coaxial rotor design is derived. Flow-field analysis reveals that the hover-optimized design employing mid-span wide chord and gradient twist configurations effectively suppresses blade tip vortex development and enhances hover efficiency. The forward-flight optimized design utilizes inner-span increasing chord and high-gradient twist designs to mitigate forward-flight blade tip vortices and profile drag power and improve propulsive efficiency， yet induces premature vortex roll-up and reduces performance in hover. A balanced optimization design， harmonizing chord gradient and twist angle distributions， synergistically balances hover/forward-flight aerodynamic performance， overcoming limitations of single-condition optimization.