Ballistic Target HRRP Fusion Recognition Combining Multi-class Relevance Vector Machine and DS

Multifeature fusion can significantly improve the recognition performance of target discrimination. A multiclass RVM model, based on the basic RVM model, is extended and DS evidence theory is used to fuse the recognition result. A HRRP (high-resolution range profile) classification approach combining MRVM and DS evidence theory is then presented. The posterior probability of multiclass RVM is integrated into the BPA (basic probability assignment). This applies the combination of RVM and DS evidence theory to target recognition and solves the difficulty of getting BPA in DS evidence theory. Experiment results based on simulated data show tthat he probability estimated by MRVM is more precise and the fusion recognition performance is better, which testifies the efficiency of the proposed method.