An intuitive systemic model based on the systemic Yoyos and stochastic differential geometry is provided for finding a meaningful geometric description of radar specific emitter identification (SEI) in this paper.We show that there is a lower dimensional state manifold which generates signals with intrinsic signatures in every emitter.Geometric significances of the manifold go far towards solving SEI problems.A recently popularized manifold learning technique

called Diffusion Maps

is said to preserve the local proximity among sampling data points by first representing the underlying manifold.So this paper examines SEI using the technique to extract diffusion features of signal instantaneous parameters for experiments on actual intercepted radar signals with several same type emitters.Finally

results illuminate the validity of features and correctness of the proposed model.