Abstract
The demand for precise navigation and guidance technologies for high-spinning flight vehicles (HFVs) has become increasingly prominent. Nonetheless, strong channel coupling and nonlinear flight dynamics pose considerable challenges to accurate rotation-rate and attitude determination using strapdown onboard sensors. To accurately estimate the rotation rate and three-axis attitude of HFVs, a ballistics-informed fast unscented Kalman filter (BUKF) is proposed. The method embeds a multi-rigid-body model into the filtering algorithm as the nonlinear state equation and constructs measurement information under multiple constraints for direct rotation-rate and three-axis attitude estimation. In addition, a posterior-covariance-driven adaptive variable step-size strategy is designed to improve computational efficiency while preserving estimation accuracy. To verify the effectiveness and robustness of the proposed algorithm, an experiment was carried out using data gathered on a flight simulation platform. Experimental results demonstrate the feasibility and effectiveness of the proposed algorithm; in comparison with conventional gyroscope integration, it achieves an order-of-magnitude improvement in accuracy and overcomes the challenges encountered in navigation and guidance within a highly dynamic satellite-denied environment.
| Original language | English |
|---|---|
| Journal | IEEE Transactions on Aerospace and Electronic Systems |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
Keywords
- High-spinning flight vehicles (HFVs)
- adaptive variable step-size strategy
- ballistics-informed fast unscented Kalman filter (BUKF)
- three-axis attitude
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