Abstract: Range profile is one of the most important features in UWB radar target recognition. The mathematical model of ballistic target micro-motion time-profile is derived. Then the translation-invariant features of central moment and bispectrum are extracted from HRRPs. After feature dimensionality reduction with K-L transform and local bispectrum respectively, these features are classified by LS-SVM. Finally, ballistic target recognition on decision level fusion is done. The simulation results show that proposed method combined with these two features achieves good recognition performance and is low sensitive to Gausses white noise compared with the single feature recognition method.