许多涉及四旋翼的空中任务既要求即时响应能力，又需长时域规划以实现避障、能量效率优化或轨迹跟踪。高保真度模型可实现精确控制，但计算速度无法满足长时域需求；低保真度规划器虽具备良好可扩展性，却无法直接驱动系统，因而需采用级联架构。当前主流的分层方法使用简化模型进行规划，并依赖高保真度控制器执行跟踪，但此类分解本质上存在次优性：控制器受限于粗糙的规划结果，而传统MPC方案则通过缩短时域以保障实时性。本文提出UNIQUE——一种以时间级联替代分层堆叠的MPC架构。其中，规划问题被建模为单一多阶段MPC的第二尾部时域，而非独立求解。我们统一了不同时域的成本函数，为质点规划模型推导出可行性约束，并引入状态转换约束，将高保真度状态映射为具有物理意义的低保真度状态。通过并行运行质点模型求解器与混合整数求解器处理非凸性，并在规划时域内逐步实施三维障碍物平滑。仿真与真实飞行实验表明，在相同计算资源预算下，UNIQUE相较标准MPC及分层基线方法，闭环跟踪性能提升最高达75%。消融实验与帕累托分析进一步验证了该方法在时域长度、约束近似方式及平滑调度等不同变体下的性能优势。

Many aerial tasks involving quadrotors demand both instant reactivity and long-horizon planning for obstacle avoidance, energy efficiency, or trajectory tracking. High-fidelity models enable accurate control but are too slow for long horizons. Low-fidelity planners scale but cannot directly control the system, necessitating cascaded architectures. Prevailing hierarchical approaches plan with a simplified model and use a high-fidelity controller for tracking, yet this decomposition is inherently suboptimal. The controller is limited by the coarse plan, and conventional MPC alternatives shorten the horizon to stay real-time feasible. We present UNIQUE, an MPC architecture that replaces this hierarchical stacking with temporal cascading. The planning problem is formulated as the second-tail horizon of a single multi-phase MPC, rather than being solved separately. We align costs across horizons, derive feasibility constraints for the point-mass planning model, and introduce transition constraints that convert high-fidelity states into meaningful low-fidelity states. Parallel point-mass and mixed-integer solvers address nonconvexities while incorporating progressive 3D obstacle smoothing over the planning horizon. In simulations and real flights, under equal computational budgets, UNIQUE improves closed-loop tracking by up to 75% compared with standard MPC and hierarchical baselines. Ablations and Pareto analyses confirm performance gains across variations in horizon, constraint approximations, and smoothing schedules.