SMALL-SHAPED SPACE TARGET RECOGNITION BASED ON WAVELET DECOMPOSITION AND SUPPORT VECTOR MACHINE

摘要

A kind of method for small-shaped space target recognition was proposed in this paper based on feature extraction with wavelet decomposition and Formative Support Vector Machine (FSVM) with Sequential Minimal Optimization (SMO) algorithm. Firstly, the significance and characteristics of space target recognition were discussed and a two-stage recognition strategy was designed. And then aiming at the characteristics of small-shaped space target recognition, a new method was implemented based on feature extraction with wavelet decomposition and FSVM with SMO algorithm. Simulation results show the good performance of the algorithm proposed in this paper: the correct rate is more than 97% within 1360 simulation samples of ten classes of small shaped space targets; meanwhile the algorithm is characterized with high speed of near real time in both implementation of training and testing.