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Geomagnetic Vector Navigation Based on Interactive Marginalized Particle Filter
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AI
DOI：10.1109/TGRS.2026.3664099.png)
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Abstract
En 中文
Aeromagnetic vector navigation has the potential to significantly improve the autonomous navigation of the aircraft, especially for low-altitude aircraft, in the environment of restricted or denied satellite positioning. Fusing geomagnetic vector measurements with inertial navigation data enables joint estimation and correction of INS error states. The key to high-precision geomagnetic vector navigation is to realize the cooperative correction of position and attitude errors of the navigation system through a geomagnetic vector navigation filter, which significantly reduces the influence of vehicle space position and attitude errors on geomagnetic vector measurement, and then obtains high-precision position and attitude estimation. However, the nonlinear and non-Gaussian characteristics are superimposed with large initial position error and magnetic measurement error, which makes it difficult to maintain high accuracy and stability of geomagnetic vector navigation filtering. To solve the above problems, a geomagnetic vector navigation strategy based on interactive marginalized particle filter (IMPF) is proposed. The two-component geomagnetic matching that is insensitive to heading errors is combined with the marginalized particle filter (MPF) framework. The MPF framework enables accurate estimation of the navigation error-state vector under nonlinear and non-Gaussian conditions. In addition, considering the comprehensive magnetic measurement error term and the two-component geomagnetic matching position constraint, the filter parameters are adaptively modified, thus improving the robustness of the geomagnetic vector navigation filter to the initial position error of the vehicle and the magnetic measurement error. The above geomagnetic vector navigation strategy can realize the cooperative optimal estimation of vehicle position and attitude under large initial position error and magnetic measurement error. The semi-measured driving simulation experiment based on the measured geomagnetic vector maps shows that this method can achieve higher accuracy and stability of geomagnetic navigation.
Keywords:
Geomagnetic vector navigation
interactive marginalized particle filtering
low-altitude aircraft
two-component geomagnetic matching
Journal
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8.6
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10.7W