Star pattern recognition is one of the key problems of the celestial navigation. The traditional
star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are
a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high.
Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent,
especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be
estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition
can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star
pattern recognition algorithm include at least the improved matching speed and the improved success rate.
In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars
on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern
recognition is established in real time dynamically. The star images extracted in the camera plane are matched
in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing
the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated
by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and
its matching success rate is improved greatly.