LAUSR

In this paper, a new algorithm called blind star identification is presented to identify the stars in night sky images without using the intrinsic parameters of the star sensor camera (focal length, principal point, and pixel size), and in lost in space mode. The accuracy and reliability of the proposed algorithm were successfully validated by using the real night sky images and Monte Carlo simulations. Accordingly, the proposed algorithm was successfully able to identify in more than 90% of the images containing more than five stars and no wrong identification was observed in the Monte Carlo simulations. On the other hand, the rotation around the optical axis, which cannot be estimated using vector observations, should be minimized in the process of designing and manufacturing the star sensor and carefully measured in the ground calibration, like as the aberration and lens distortion. Ultimately, another advantage of this algorithm is the simultaneous use of planar and interstellar angles. This advantage leads to data redundancy and greater reliability of the algorithm so that the performance of the algorithm is guaranteed under severe error conditions.