Abstract：With the continuous development of the space exploration, the number of space objects is increasing and the space situation is becoming complex. It is imperative to improve the space objects identification technology to enhance the space situational awareness. The space objects intelligent identification architecture based on data-driven is designed, and two kinds of machine learning algorithms, Gradient Boosting Decision Tree (GBDT) and Convolutional Neural Network(CNN), are utilized respectively to construct identification models by utilizing massive characteristics data. The experimental results show that the recognition accuracy of the two models reaches more than 90 %, which can provide an effective solution for intelligent identification of space objects.
王文竹，李 智，来嘉哲，徐 灿. 基于数据驱动的空间目标智能识别[J]. 指挥与控制学报, 2019, 5(1): 25-30.
WANG Wen-Zhu, LI Zhi, LAI Jia-Zhe, XU Can. Space Objects Intelligent Identification Based on the Data-Driven Method. Journal of Command and Control, 2019, 5(1): 25-30.
2019, Vol. 5 
