Bin Jia, Inteeligent Fusion Technology Inc, Khanh D. Pham, Air Force Research Lab, Erick Blasch, Air Force Research Lab, Dan Shen, Intelligent Fusion Technology Inc., Zhonghai Wang, Intelligent Fusion Technology Inc., Genshe Chen, Intelligent Fusion Technology Inc.,
Keywords: Space Object Classification; Light curve; Energy; Clustering; Support Vector Machine, Information Fusion.
Abstract:
In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.
Date of Conference: September 19-22, 2017
Track: Poster