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About this paper
Giulio Delama, Martin Scheiber, Yixiao Ge, Tarek Hamel, Stephan Weiss, Robert Mahony
A novel Equivariant Filter, leveraging Galilean symmetry, enables consistent online joint estimation of navigation states and unknown time delays in Inertial Navigation Systems. It exhibited superior consistency and stability in simulations with delays up to 500 ms, where EKF-based alternatives diverged, and successfully tracked real-world UAV GNSS delays.
Key insights
- The Galilean matrix Lie group provides a natural geometric framework to model inertial motion with explicit temporal offsets, enabling a coupled representation of space and time for state estimation.
- Equivariant Filters (EqFs) are more inherently consistent and stable for joint state and time-delay estimation compared to traditional EKFs, particularly when dealing with the non-linear coupling introduced by unknown delays.
- Efficient IMU preintegration, adapted to account for estimated time delays through a sliding buffer, is crucial for consistently bridging measurement gaps and enabling robust online estimation.
Summary by alphaXiv.
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