Autonomous determination of unknown characteristics of an asteroid using optical and altimeter information

As to the deep space exploring mission, such as flyby, rendezvous, landing and returning samples to an asteroid, it is important to estimate the motion and shape of the target body. During the approaching process, the distance information can be obtained by the altimeter in that the distance is quite close. At the same time we can also obtain images of the target body using the onboard navigation camera. Thus, a simple, reliable, and fast algorithm is developed to estimate the direction of spin axis, the spin rate and the feature point radius. Here we assume that both of the motion of the asteroid and the spacecraft are uniform linear motion, if we limit the time of observation. Based on the assumption, it is valid that after observing the feature point four times at the same interval, we can get four observation vectors which can express the relative position and velocity of the spacecraft and the spin rate and feature point radius of the asteroid. So it is feasible that the information obtained from images of the feature point and the altimeter in the course of approaching can be processed by the algorithm, through a Extended Kalman Filter to update the target relative state information and get the characteristics of an asteroid.. The validity of the proposed method is verified by performing the Monte Carlo simulations. These simulations incorporate errors in the initial states. The results prove that the algorithm is successful in estimating the spin rate and radius of feature point.