A NEW DIGITAL MODULATION RECOGNITION METHOD USING FEATURES EXTRACTED FROM GAR MODEL PARAMETERS
从GAR模型参数提取特征的数字调制识别新方法

A new digital modulation recognition method is proposed, which is based on the features extracted from generalized autoregressive (GAR) model parameters of the obsevered sequence and the use of neural network classifier. Because of the better noise suppression capacity of the GAR model and the powerful pattern classification capacity of the neural network classifier, the new method can significantly improve the recognition performance in lower SNR. Computer simulations also show that the new method possesses higher recognition ratio and better robustness.