Open AccessRelative navigation technique with constrained GNSS data for formation‐flying CubeSat mission, CANYVAL‐C
Author(s) -
Lee Eunji,
Son Jihae,
Park SangYoung
Publication year - 2021
Publication title -
navigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.847
H-Index - 46
eISSN - 2161-4296
pISSN - 0028-1522
DOI - 10.1002/navi.439
Subject(s) - extended kalman filter , cubesat , gnss applications , kalman filter , covariance , computer science , robustness (evolution) , control theory (sociology) , engineering , aerospace engineering , global positioning system , mathematics , artificial intelligence , telecommunications , biochemistry , statistics , chemistry , satellite , control (management) , gene
This study introduces and verifies a relative navigation technique for two CubeSats in formation flying as part of the CANYVAL‐C mission. Because the mission requires precision and robustness subject to restricted computational complexity, the technique employs an Extended Kalman Filter (EKF) and raw GNSS data to achieve relative navigation. The relative navigation technique is composed of two parts: parameter‐tuning using an Adaptive Kalman Filter (AKF) in a ground station, and the application of the adaptively determined parameters to allow onboard EKF. Based on Hardware‐in‐the‐Loop Simulations (HILS), the relative positioning error of the EKF with adaptively determined parameters ranged from 10 to 20 cm on each axis (3σ) and satisfied the mission requirement of 1 m. The simulations confirm that the technique yields reliable relative navigation and a realistic error covariance without imposing a computational burden on the CubeSat, as well as reduces the time required for parameter tuning.