Research On Intelligent Classification And Identification Of C - Band Radio Signal

Radio spectrum resources is an important national strategic resource. Radio spectrum resources are not inexhaustible public resources, and its limited increasingly prominent. The human demand for radio spectrum resources is rapidly expanding and competitive various radio technologies and applications become more intense, so that the scarcity of radio spectrum resources continue to increase, not all kinds of interference signal segment increased. In order to better radio spectrum management and monitoring, through technical means to monitor the radio signals of intelligent classification and recognition on the show is extremely important for accurate classification of radio signals more practical significance.In this paper, using different feature extraction methods for C-band radio signal feature extraction and use back propagation learning algorithm to do intelligent classifier to classify C-band radio signal recognition. The main contents are as follows:1. Introduction What is C-band radio signals, and describes the principal components analysis, Back propagation learning algorithm design principles and mathematical models.2. Study of feature extraction methods, due to the huge amount of data radio signal data of high dimensionality, we use a method based on principal components analysis and frequency domain features and statistic characteristics of feature extraction of C-band radio signal feature extraction.3.using back propagation learning algorithm as an intelligent classifier to classify the identification of the C-band radio signal, for selecting the parameters of back propagation learning algorithm is analyzed, and the use of different methods of feature extraction signal input back propagation learning algorithm classifier model simulation, good recognition results.