为了解决高分辨率距离像 (HRRP)分类的姿态敏感和距离像对齐问题 ,基于连续小波变换 (CWT)的自相似特性 ,构造了能量尺度分形维数。分别在 3个极化测量通道和两个尺度区间上 ,从 HRRP的 CWT能量随尺度的演化过程中提取了原始特征集。采用 Fisher可分性准则作判据 ,进一步确定了 3维最佳特征向量。并从理论和实验上证明了 ,能量尺度分形维数特征较不敏感于噪声和目标方位角的变化 ,同时不受目标径向位移和距离像平移的影响 ,是性能良好的飞机目标分类特征 In order to solve the attitude sensitive and distance image alignment problems of high resolution range image (HRRP) classification, energy scale fractal dimension is constructed based on the self-similar properties of continuous wavelet transform (CWT). The original feature set was extracted from the evolution of CWT energy of HRRP along the scale in three polarization measurement channels and two scale intervals, respectively. Using the Fisher divisibility criterion as the criterion, the 3-D best feature vector is further determined. It is proved theoretically and experimentally that the fractal dimension features of energy scale are less sensitive to the changes of noise and azimuth of targets, and are not subject to target radial displacement and distance image shift. They are good target classification features of aircraft