  CubeSats have become a meaningful option for deep-space exploration, but
their autonomy must be increased to maximize the science return while limiting
the complexity in operations. We present here a solution for an autonomous
orbit determination in the context of a CubeSat cruising in deep space. The
study case is a journey from Earth to Mars. An optical sensor at CubeSat
standard is considered. The image processing is added to extract the direction
of distant celestial bodies with 0.2 arcsec accuracy: it consists of a Multiple
Cross-Correlation (MCC) algorithm that uses bright stars in the background of
the images. Then, an Unscented Kalman Filter (UKF) is built to perform an
asynchronous triangulation from the successive directions of the celestial
bodies. The UKF meets the expected performance in contexts where linear
approximations are not possible. The orbit reconstruction reaches a 3-sigma
accuracy of 30 km in the middle of the Earth-Mars cruise. Additionally, the CPU
cost of the filter is assessed at less than 1 second per iteration with a
typical CubeSat hardware. It is ready for further improvements in terms of new
observables associated with data fusion, quicker convergence and attitude
control savings.
