Algorithm enhances navigation performance in near-Earth flight vehicles by correcting atmospheric density errors.
Inaccurate stellar atmospheric refraction models impair the attainable accuracy of the refraction-based celestial navigation, leading to performance degradation in Strapdown Inertial Navigation System/Refractive Celestial Navigation System (SINS/RCNS) integrated navigation. This paper proposes a new SINS/RCNS integrated navigation algorithm aided by dual-band starlight refraction observations for near-Earth flight vehicles. In an analogy with the dual-frequency error correction in GNSS positioning, this algorithm exploits dual-band starlight measurements to estimate the atmospheric density error. Then, the measurement equation is established between the dual-band refraction angles and both position error and atmospheric density error. Moreover, the Extended Kalman Filter (EKF) is utilized to estimate the atmospheric density error online, which is then used for navigation error compensation. The simulation results indicate that the proposed algorithm can effectively mitigate navigation accuracy degradation by online correction for the atmospheric density error, enhancing integrated navigation performance for near-Earth flight applications.
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Wang et al. (2025) studied this question.
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