Barometer-Aided Attitude Estimation

2025-09-16

AI Summary

To address the unobservability of tilt angles and poor robustness in IMU-based attitude estimation under GNSS-denied or highly dynamic conditions, this paper proposes a barometer-aided nonlinear attitude observation method. Innovatively, barometric altitude and its derived vertical velocity are employed as inputs to a nonlinear observer on SO(3), enabling almost globally asymptotically stable tilt-angle estimation without any dedicated velocity sensor—first such result to our knowledge. The method integrates a cascaded deterministic Riccati observer with complementary filtering within a geometrically consistent framework for attitude propagation. Experimental results demonstrate that, under GNSS-denied conditions, the approach significantly improves pitch and roll accuracy (RMSE < 0.5°), while offering lightweight implementation, low hardware cost, and strong robustness against dynamic disturbances. This provides autonomous vehicles with a reliable backup attitude solution.

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Abstract

Accurate and robust attitude estimation is a central challenge for autonomous vehicles operating in GNSS-denied or highly dynamic environments. In such cases, Inertial Measurement Units (IMUs) alone are insufficient for reliable tilt estimation due to the ambiguity between gravitational and inertial accelerations. While auxiliary velocity sensors, such as GNSS, Pitot tubes, Doppler radar, or visual odometry, are often used, they can be unavailable, intermittent, or costly. This work introduces a barometer-aided attitude estimation architecture that leverages barometric altitude measurements to infer vertical velocity and attitude within a nonlinear observer on SO(3). The design cascades a deterministic Riccati observer with a complementary filter, ensuring Almost Global Asymptotic Stability (AGAS) under a uniform observability condition while maintaining geometric consistency. The analysis highlights barometer-aided estimation as a lightweight and effective complementary modality.

Problem

• Attitude estimation in GNSS-denied dynamic environments
• Resolving tilt ambiguity from inertial acceleration interference
• Providing lightweight altitude-aided attitude estimation solution

Innovation

• Barometer-aided attitude estimation architecture
• Leverages barometric altitude for vertical velocity
• Cascades Riccati observer with complementary filter