Abstract
This paper presents a new Strap-down Inertial Navigation System/Spectrum Red-Shift/Star Sensor (SINS/SRS/SS) system integration methodology to improve the autonomy and reliability of spacecraft navigation using the spectrum red-shift information from natural celestial bodies such as the Sun, Jupiter and the Earth. The system models for SINS/SRS/SS integration are established. The information fusion of SINS/SRS/SS integration is designed as the structure of the federated Kalman filter to fuse the local estimations of SINS/SRS and SINS/SS integrated subsystems to generate the global state estimation for spacecraft navigation. A new robust adaptive unscented particle filter is also developed to obtain the local state estimations of SINS/SRS and SINS/SS integrated subsystems in a parallel manner. The simulation results demonstrate that the proposed methodology for SINS/SRS/SS integration can effectively calculate navigation solutions, leading to strong autonomy and high reliability for spacecraft navigation.
Highlights
Considerable research efforts have been dedicated to spacecraft navigation, resulting in various navigation techniques such as ground radio navigation, satellite navigation system, inertial navigation system (INS) and celestial navigation system [1,2]
This paper presents a new methodology for a SINS/spectrum red-shift (SRS)/SS autonomous integrated navigation system to improve the autonomy, reliability and accuracy of spacecraft navigation
This paper presents a new methodology of SINS/SRS/SS integration for spacecraft navigation
Summary
Considerable research efforts have been dedicated to spacecraft navigation, resulting in various navigation techniques such as ground radio navigation, satellite navigation system, inertial navigation system (INS) and celestial navigation system [1,2]. The velocity of the spacecraft can be obtained from the spectral information (celestial ephemeris) of the solar system, without requiring any information on ground radio and relying on spacecraft orbital dynamics equations This method has the merits of simple implementation, high precision, strong autonomy and excellent real-time performance [11,12,13], leading to a promising solution to improve the autonomy of spacecraft navigation. Sensors 2018, 18, x FOR PEER REVIEW concept of robust adaptive filtering in UPF to prevent particles from degeneracy It uses the equivalent weight function and adaptive factor to improve the importance sampling resulted from unscented transformation based on the information of system state and measurement models. Its navigation coordinate system is chosen as East-North-Up (E-N-U) geographic coordinate system
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