This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.

    Design/methodology/approach

    To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.

    Findings

    Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.

    Originality/value

    A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.


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    Title :

    Integrated autonomous optical navigation using Q-Learning extended Kalman filter


    Contributors:
    Xiong, Kai (author) / Wei, Chunling (author) / Zhou, Peng (author)

    Published in:

    Publication date :

    2022-02-14


    Size :

    1 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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