Article detail · 2019
Nontraditional Attitude Filtering with Simultaneous Process and Measurement Covariance Adaptation
Journal
Journal of Aerospace Engineering- Year
- 2019
- Type
- article
Data source split
- YÖKSİS venue Journal of Aerospace Engineering
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
This study discusses simultaneous adaptation of the process and measurement noise covariance matrixes for a nontraditional attitude filtering algorithm. The nontraditional attitude filtering algorithm integrates the singular value decomposition (SVD) method with the unscented Kalman filter (UKF) to estimate the attitude of a nanosatellite. The SVD method uses magnetometer and Sun sensor measurements as the first stage of the algorithm and estimates the attitude of the nanosatellite, giving one estimate at a single frame. Then these estimated attitude terms are used as input to an adaptive UKF. The conventional UKF and the proposed adaptive UKF were compared with demonstrations of the attitude and attitude rate estimation of the satellite. Specifically, the Q (process noise covariance)-adaptation method is proposed. In the case of process noise increment, which may be caused by the changes in the environment or satellite dynamics, the performance of the Q-adaptive UKF was investigated.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
14 citations
OpenAlex cited_by_count (cache / database)
8 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Satellite attitude estimation using SVD-Aided EKF with simultaneous process and measurement covariance adaptation 2021
- Attitude filtering with uncertain process and measurement noise covariance using SVD‐aided adaptive UKF 2023
- SVD-Aided UKF Adaptation for Nanosatellite Attitude Estimation under Uncertain Process Noise Conditions 2024
- Influence of Process Noise Biases to Satellite Attitude Filters’ Estimates 2024
- Q-adaptive AKF for Estimation of UAV dynamics in the Case of Biased Process Noise 2024
- Adaptive filtering-based relative navigation for formation-flying satellites 2026
- Multiple Fading Factors Based Adaptive SVD-aided UKF for Small Satellite Attitude Estimation 2023
- SVD-Aided EKF with Process Noise Covariance Adaptation Applied to Satellite Attitude Dynamics 2021