A hybrid filtering approach for real-time magnetometer calibration: Algorithm design and validation using in-orbit data
Acta Astronautica, cilt.249, ss.1127-1137, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 249
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.actaastro.2026.08.015
- Dergi Adı: Acta Astronautica
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Public Affairs Index, Academic Search Ultimate (EBSCO)
- Sayfa Sayıları: ss.1127-1137
- Anahtar Kelimeler: Attitude determination, Kalman filter, Nanosatellites, Onboard calibration, Three-axis magnetometer
- Orta Doğu Teknik Üniversitesi Adresli: Evet
Özet
Reliable attitude determination for low Earth orbit (LEO) nanosatellites depends on three-axis magnetometers. However, their measurements are often degraded by bias, scale factor, non-orthogonality, and installation misalignments. To address these sensor errors in real-time onboard applications, this paper proposes a hybrid cascaded calibration architecture that decouples the estimation of linear calibration parameters from sensor-to-body misalignment errors. First, a linear Kalman filter (LKF) estimates bias, scale factor, and non-orthogonality. Subsequently, an unscented Kalman filter (UKF) uses pre-calibrated measurements to estimate nonlinear sensor-to-body misalignments as Euler angles. The architecture is validated using 6U nanosatellite simulations and in-orbit telemetry from the Connecta IoT-15 and IoT-16 satellites during spin maneuvers. The results show that the LKF + UKF architecture provides robust calibration performance and physically interpretable misalignment estimates, while achieving vector-calibration accuracy comparable to TWOSTEP in the tested cases.