Unmanned aerial vehicle (UAV) clusters offer enhanced resilience, coverage and mission flexibility but demand robust state estimation to counter disturbances and uncertainties. This paper proposes a distributed algorithm that fuses a Quaternion‑based Unscented Kalman Filter (QUKF) with a Generalized Proportional‑Integral Observer (GPIO) for improved state estimation. The decentralized design ensures scalability and fault tolerance across large formations, while the GPIO compensates for linearization errors, sharpening quaternion accuracy. Accurate state estimates are then integrated into cooperative control laws to maintain stable formation and ensure trajectory convergence. Simulations confirm that this approach achieves precise trajectory tracking and formation synchronization under sensor noise and model uncertainties.