Abstract: Aiming at the attitude measurement of a space non-cooperative target, a vision measurement method of non-cooperative target based on convolutional neural network is designed. Firstly, a feature extraction network is pre-trained on open dataset, then a few actual target images are used for transfer learning, thus realizing an automatic extraction of the high-level abstract features of the non-cooperative target images. Secondly, a regression model based attitude mapping network is designed, which builds a nonlinear relationship between the high-level features of image and three-axis attitude angle to realize the attitude measurement of the non-cooperative target. The measurement accuracy and parameter size of the two kinds of feature extraction networks are verified by experiments, with the networks’ accuracy reaching 0.711 degrees (1σ), the feasibility of method, “monocular camera+convolutional neural network”, is proved.

Key words: Convolutional neural network, Space non-cooperative target, Monocular vison, Attitude measurement