Robust Integrated Orbit and Attitude Estimation Using Geophysical Data

Abstract Geophysical information such as the Earth geomagnetic field and gravity gradient (GG) data can provide a basis for autonomous concurrent orbit and attitude estimation (COAE) of satellites in low earth orbits (LEO), as magnetometers and gravity gradiometer measurements are in general functions of time, position as well as the vehicle's orientation. While gradiometer has recently been investigated just for orbit estimation (OE), the current study is focused on COAE via only utility of the GG data. To this aim, observability conditions are analyzed, where the sensitivity of the proposed COAE approach with respect to various system and roto-translational elements is also examined. Considering the nonlinear nature of the COAE problem, a modified robust unscented Kalman filter is adopted for state estimation that is enhanced by innovation-based fading factors to be robust against the modeling errors. Subsequently, a centralized fusion of GG and three-axis magnetometer (TAM) measurement data is employed to improve the accuracy and reliability of the proposed approach for space navigation. The results obtained from numerical test cases confirm feasibility and effectiveness of the proposed technique for complete COAE of space navigation in LEO satellites.