A new classification algorithm based on multi-kernel support vector machine (SVM) was proposed for classification problems on infrared cloud background image. The experimental results show that the method integrates the advantages of polynomial kernel functions, Gaussian radial kernel functions and multilayer perception kernel functions. Compared with the traditional single-kernel SVM classification method, the proposed method has better performance both in local interpolation and global extrapolation, and is more suitable for SVM classification problems when the training sample size is small. Experimental results show the superiority of the proposed algorithm..
A motion model for the hypersonic boost-glide aircraft(HBG) was proposed in this paper, which also analyzed the precision of model through simulation. Firstly the trajectory of HBG was analyzed, and a scheme which divide the trajectory into two parts then build the motion model on each part. Secondly a restrained model of boosting stage and a restrained model of J2 perturbation were established, and set up the observe model. Finally the analysis of simulation results show the feasible and high-accuracy of the model, and raise a expectation for intensive research.
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