具有几乎全局渐近稳定性保证的皮托管辅助姿态与空速估计
Pitot-Aided Attitude and Air Velocity Estimation with Almost Global Asymptotic Stability Guarantees
AI总结：
提出一种级联观测器结构，利用IMU和皮托管测量实现固定翼无人机姿态与空速的几乎全局渐近稳定估计，通过Riccati/Kalman滤波和SO(3)非线性观测器，在均匀可观测条件下证明稳定性，并用真实飞行数据验证。
摘要：
本文研究了使用IMU测量和至少一个皮托管测量，具有几乎全局渐近稳定性（AGAS）保证的固定翼无人飞行器（UAV）姿态和空速估计问题。开发了一种级联观测器结构，其中Riccati/Kalman型滤波器以IMU数据为输入、皮托管测量为输出，估计体坐标系空速和飞行器倾斜角。在温和激励条件下，所得空速和倾斜估计误差动态被证明是均匀可观测的。然后将估计的倾斜角与磁力计测量结合，在SO(3)上的非线性观测器中恢复完整姿态。严格分析建立了在均匀可观测性（UO）条件下整个级联结构的AGAS。通过在实际飞行数据上的验证，证明了所提方法的有效性。
英文摘要：
This paper investigates the problem of attitude and air velocity estimation for fixed-wing unmanned aerial vehicles (UAVs) using IMU measurements and at least one Pitot tube measurement, with almost global asymptotic stability (AGAS) guarantees. A cascade observer architecture is developed, in which a Riccati/Kalman-type filter estimates the body-fixed frame air velocity and the vehicle's tilt using IMU data as inputs and Pitot measurements as outputs. Under mild excitation conditions, the resulting air velocity and tilt estimation error dynamics are shown to be uniformly observable. The estimated tilt is then combined with magnetometer measurements in a nonlinear observer on SO(3) to recover the full attitude. Rigorous analysis establishes AGAS of the overall cascade structure under the uniform observability (UO) condition. The effectiveness of the proposed approach is demonstrated through validation on real flight data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
