Recursive Star-Identification Algorithm Using An Adaptive Singular-Value-Decomposition-Based Angular-Velocity Estimator

This paper describes an algorithm obtained by merging a recursive star-identification algorithm with a recently developed adaptive singular-value-decomposition-based estimator of the angular-velocity vector (QuateRA). In a recursive algorithm, the more accurate the angular-velocity estimate is, the quicker and more robust to noise is the resultant recursive algorithm. Hence, combining these two techniques produces an algorithm capable of handling a variety of dynamics scenarios. The speed and robustness of the algorithm are highlighted in a selection of simulated scenarios. First, a speed comparison is made with the state-of-the-art lost-in-space star-identification algorithm, Pyramid. This test shows that in the best case, the algorithm is on average an order of magnitude faster than Pyramid. Next, the recursive algorithm is validated for a variety of dynamic cases, including a ground-based "Stellar Compass" scenario, a satellite in geosynchronous orbit, a satellite during a reorientation maneuver, and a satellite undergoing non-pure-spin dynamics.