Attitude Estimation Using Inertial and Barometric Measurements

2026-07-14

AI Summary

This work addresses the challenge of attitude estimation under GNSS-denied and highly dynamic flight conditions, where inertial measurement unit (IMU)-only approaches suffer from ambiguity between gravitational and inertial accelerations. To overcome this limitation, the paper proposes a nonlinear attitude estimation algorithm that fuses barometric altitude measurements. Two novel observers on SO(3) are developed: the first employs a cascaded structure combining a Riccati observer with complementary filtering to achieve almost global asymptotic stability, while the second constructs a unified observer on SO(3)×ℝ² that relaxes observability requirements and ensures local exponential stability. Notably, the method eliminates the need for conventional velocity sensors by leveraging barometric data to enhance vertical motion awareness. Evaluation on both simulated and real flight data demonstrates that the proposed approach delivers lightweight, reliable, and efficient attitude estimation performance.

Abstract

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.

Problem

• attitude estimation
• inertial measurement
• barometric altitude
• GNSS-denied
• autonomous vehicles

Innovation

• barometer-aided attitude estimation
• nonlinear observer on SO(3)
• almost-global asymptotic stability
• uniform observability
• inertial navigation