Radar high resolution range profile (HRRP) identification in radar automatic target recognition based on an adaptive evolutionary particle swarm optimization (AEPSO) optimizing support vector machine (SVM) target classifier method is proposed. To enhance the learning ability of particles in the evolution process, the proposed method, using the staged adjustment acceleration factor, adapts to the nonlinear variation of the particle optimization by an adaptive inertia weight. According to introducing local search operators, the particle diversity, to avoid the local optimal trap, is increased effectively. The SVM parameters are optimized by the improved PSO algorithm to establish a classification recognizer model. The AEPSO-SVM model is applied to radar HRRP target recognition, and the simulation results demonstrate that the proposed method has better accuracy and robustness.