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讨论了信号中奇异性的测度——Ｌｉｐｓｃｈｉｔｚ指数，分析了子波变换与Ｌｉｐｓｃｈｉｔｚ指数的内在联系，给出了使用子波变换计算信号的Ｌｉｐｓｃｈｉｔｚ指数的方法以及Ｌｉｐｓｃｈｉｔｚ指数在实际应用中的物理背景和意义。结合Ｌｉｐｓｃｈｉｔｚ指数及其检测方法，对三类飞机的雷达回波数据进行了实验模拟。通过计算回波波元的Ｌｉｐｓｃｈｉｔｚ指数来构造特征向量，并使用人工神经网络进行分类识别，给出识别的模拟结果。结果表明检测雷达回波波元的Ｌｉｐｓｃｈｉｔｚ指数进行雷达目标识别是一个有效的尝试。
The measure of singularity in signal is discussed - the Lipschitz index. The intrinsic relationship between wavelet transform and Lipschitz index is analyzed. The method of calculating the Lipschitz index of signal using wavelet transform and the physical background of Lipschitz index in practice are given. significance. Combined with Lipschitz index and its detection method, the radar echo data of three types of aircraft were experimentally simulated. The eigenvector is constructed by computing the Lipschitz exponent of the echo wave element, and the classification is made by artificial neural network. The simulation results are given. The results show that detecting Lipschitz exponents of radar echoes for radar target recognition is an effective attempt.