Star sensor is an avionics instrument used toprovide the absolute 3-axis attitude of a spacecraft by utiliz-ing star observations. The key function is to recognize theobserved stars by comparing them with the referenc...Star sensor is an avionics instrument used toprovide the absolute 3-axis attitude of a spacecraft by utiliz-ing star observations. The key function is to recognize theobserved stars by comparing them with the reference cata-logue. Autonomous star pattern recognition requires thatsimilar patterns can be distinguished from each other with a small training set. Therefore, a new method based on neural network technology is proposed and a recognition systemcontaining parallel backpropagation (BP) multi-subnets isdesigned. The simulation results show that the method per-forms much better than traditional algorithms and the pro-posed system can achieve both higher recognition accuracyand faster recognition speed.展开更多
The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift...The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively acceldrate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm.展开更多
文摘Star sensor is an avionics instrument used toprovide the absolute 3-axis attitude of a spacecraft by utiliz-ing star observations. The key function is to recognize theobserved stars by comparing them with the reference cata-logue. Autonomous star pattern recognition requires thatsimilar patterns can be distinguished from each other with a small training set. Therefore, a new method based on neural network technology is proposed and a recognition systemcontaining parallel backpropagation (BP) multi-subnets isdesigned. The simulation results show that the method per-forms much better than traditional algorithms and the pro-posed system can achieve both higher recognition accuracyand faster recognition speed.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61172138 and 61401340)the Open Research Fund of the Academy of Satellite Application,China(Grant No.2014 CXJJ-DH 12)+3 种基金the Fundamental Research Funds for the Central Universities,China(Grant Nos.JB141303 and201413B)the Natural Science Basic Research Plan in Shaanxi Province,China(Grant No.2013JQ8040)the Research Fund for the Doctoral Program of Higher Education of China(Grant No.20130203120004)the Xi’an Science and Technology Plan,China(Grant.No CXY1350(4))
文摘The log-polar transform （LPT） is introduced into the star identification because of its rotation invariance. An improved autonomous star identification algorithm is proposed in this paper to avoid the circular shift of the feature vector and to reduce the time consumed in the star identification algorithm using LPT. In the proposed algorithm, the star pattern of the same navigation star remains unchanged when the stellar image is rotated, which makes it able to reduce the star identification time. The logarithmic values of the plane distances between the navigation and its neighbor stars are adopted to structure the feature vector of the navigation star, which enhances the robustness of star identification. In addition, some efforts are made to make it able to find the identification result with fewer comparisons, instead of searching the whole feature database. The simulation results demonstrate that the proposed algorithm can effectively acceldrate the star identification. Moreover, the recognition rate and robustness by the proposed algorithm are better than those by the LPT algorithm and the modified grid algorithm.
