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Synchronous Observer Design for Inertial Navigation Systems with Almost-Global Convergence
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An Inertial Navigation System (INS) is a system that integrates acceleration and angular velocity readings from an Inertial Measurement Unit (IMU), along with other sensors such as Global Navigation Satellite Systems (GNSS) position, GNSS velocity, and magnetometer, to estimate the attitude, velocity, and position of a vehicle. This paper shows that the INS problem can be analysed using the automorphism group of the extended special Euclidean group: a group we term the extended similarity group . By exploiting this novel geometric framework, we propose a synchronous observer architecture; that is, an observer architecture for which the observer error is stationary if the correction terms are set to zero. In turn, this enables us to derive a modular, or plug-and-play, observer design for INS that allows different sensors to be added or removed depending on what is available in the vehicle sensor suite. We prove both almost-global asymptotic and local exponential stability of the error dynamics for the common scenario of at least IMU and GNSS position. To the authors' knowledge, this is the first non-linear observer design with almost global convergence guarantees or with plug-and-play modular capability. A simulation with extreme initial error demonstrates the almost-global robustness of the system. Real-world capability is demonstrated on data from a fixed-wing UAV, and the solution is compared to the state-of-the-art ArduPilot INS.
Forward citations
Cited by 2 Pith papers
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Classification of Linear Observed Systems on Multi-Frame Groups via Automorphisms
All group-affine dynamics and algebraic observations on multi-frame groups are classified via automorphisms, extending two-frame group theory to coupled multi-frame navigation.
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Observer Design for Optical Flow-Based Visual-Inertial Odometry with Almost-Global Convergence
A cascaded observer combining a globally exponentially stable Riccati filter and an almost-globally stable SO(3) complementary filter estimates velocity, gravity, and attitude from optical flow and IMU measurements.
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