Abstract: The purpose of this paper is to increase the recognition rate of projectile target.For identifying projectile target，it is necessary to extract target feature.Ballistic missile features commonly used in the scientific research work include radar cross section(RCS)feature，polarization feature，high resolution range profile(HRRP)，inverse synthetic aperture radar(ISAR)image，micro­motion feature etc.This paper mainly elaborates HRRP and micro­motion feature.In order to simplify the calculation of HRRP，we apply target scattering centers model.Ballistic missile release the decoy to avoid interception during the flight，causing warhead’s motion behaves as procession while decoy’s motion behaves as swaying.This study analyses how warhead and decoy moves when ballistic missile release the decoy and builds models for them.We process micro­motion model with short­time Fourier transform and extract the time­frequency ridge as micro­motion feature.Warhead and decoy are abundant in structure information so it is not proper to identify projectile target merely rely on one single feature.This paper puts forward a superior recognition method based on multiple feature combination，combining HRRP feature with micro­motion feature.We use principal component analysis(PCA)to reduce the dimensionality and choose support vector machine(SVM)as classification algorithm.We draw HRRP figure and multiple feature spectrum figure for the warhead and the decoy through the simulation experiment.In order to simulate the target recognition process accurately，this paper change the number of test set and create a table of comparing results.Simulation experiment shows that the recognition rate of projectile target significantly improved compared to recognition relying on one single feature.