RECURSIVE STAR-ID AND THE K-VECTOR ND
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In the context of spacecraft autonomous attitude determination, the task of star identification is to associate body-frame observed star directions with the cataloged, inertial directions. The star identification can be thought of as two distinct cases, Lost-in-space case, in which no stars in an image have been identified and no attitude estimate is available, and the recursive case, in which either at least one star has been identified, or some attitude estimate is available. The author updates a prior publication concerning recursive star identification algorithms. The first algorithm is updated to use the K-Vector ND multidimensional range search, while the second is shown to be similar to the existing Delaunay triangulation. Numerical tests are performed to compare the performance of the run-time and build-time of each algorithm. Finally, the author demonstrates how a holistic approach can be used to make design choices regarding the computational complexity of the recursive approach.