雷达回波的奇异性检测及目标识别

Detection of singularities in radar echo cell and target recognition

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 measurement of singularities in signals, Lipschitz exponents, is discussed. The inner connection between wavelet transform and Lipschitz exponents is also discussed. The method of using wavelet transform to calculate Lipschitz exponents is presented, so are the physical background and physical meaning of Lipschitz exponents. At the end of this paper, based on the data of the echoes of three kinds of planes, some experiments are done to do classification. The features are extracted by calculating the Lipschitz exponents in echo cell, and artificial neural networks (ANN) are used to classify. The results of recognition are shown, which indicate that the method of using singularities to do radar target recognition is effective.