使用惯性和气压测量进行姿态估计
Attitude Estimation Using Inertial and Barometric Measurements
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中文总结 AI 辅助
针对自动驾驶车辆姿态估计难题，介绍气压辅助姿态估计架构，设计确定性黎卡提观测器与非线性观测器，利用气压测量增强姿态估计，经模拟和实际飞行数据验证，为姿态估计提供实用补充传感方式。
中文摘要 AI 辅助
准确且稳健的姿态估计是自动驾驶车辆面临的关键挑战，尤其是在全球导航卫星系统（GNSS）信号受阻和高速飞行期间。仅惯性测量单元（IMU）在重力和惯性加速度存在模糊性时不足以进行可靠的倾斜估计。常用的辅助速度传感器可能不可用、间歇性工作或成本高昂。本文介绍了一种气压辅助姿态估计架构，利用气压高度测量提供车辆垂直运动的补充信息，增强特殊正交群（SO(3)）上非线性观测器的姿态估计。贡献有两方面。一是设计了与互补滤波器级联的确定性黎卡提观测器，在均匀可观测性条件下确保几乎全局渐近稳定性，同时保留姿态动力学的几何结构。二是提出了在SO(3)×R²上演化的非线性观测器，在统一框架内将IMU测量作为输入，气压计和磁力计测量作为输出，在宽松的均匀可观测性条件下保证局部指数稳定性。通过模拟和实际飞行数据验证了所提方法。结果表明，气压辅助估计为最小传感配置下的姿态估计提供了一种轻量级、可靠且有效的补充传感方式，在传统速度测量不可用或退化时提供了实用替代方案。
英文摘要
Accurate and robust attitude estimation is a key challenge for autonomous vehicles, particularly in GNSS-denied conditions and during highly accelerated flight. In such conditions, Inertial Measurement Units (IMUs) alone are insufficient for reliable tilt estimation due to the ambiguity between gravitational and inertial accelerations. Although auxiliary velocity sensors such as GNSS, Pitot tubes, Doppler radar, or Visual Inertial Odometry are commonly used, they may be unavailable, intermittent, or costly. This paper introduces a barometer-aided attitude estimation architecture that exploits barometric altitude measurements to provide complementary information on the vehicle's vertical motion, thereby enhancing attitude estimation within nonlinear observers on SO(3). The contributions are twofold. First, we design a deterministic Riccati observer cascaded with a complementary filter, ensuring almost-global asymptotic stability (AGAS) under a uniform observability (UO) condition while preserving the geometric structure of the attitude dynamics. Second, we propose a nonlinear observer evolving on SO(3)xR2, which integrates IMU measurements as inputs and barometer and magnetometer measurements as outputs within a unified framework, guaranteeing local exponential stability (LES) under relaxed uniform observability conditions. The proposed approaches are validated using both simulated and real flight data. The results demonstrate that barometer-aided estimation provides a lightweight, reliable, and effective complementary sensing modality for attitude estimation in minimal-sensing configurations, offering a practical alternative when conventional velocity measurements are unavailable or degraded.
发表机构
- University of Quebec in Outaouais（魁北克大学奥塔瓦分校）
- Lakehead University（湖首大学）
- I3S-UniCA-CNRS, University Cote d’Azur（蔚蓝海岸大学I3S - 法国国家科学研究中心联合实验室）
机构由 AI 辅助整理，请以论文原文为准。
