A New Intelligent Approach for Recognition of Digital Satellite Signals

Abstract

In this paper a novel automatic method to identify digital communication signals is presented for different signal to noise ranges (SNRs). The method is based on the idea of optimization of the adaptive neuro-fuzzy inference system (ANFIS) including three major modules: the feature extraction the classification and optimization module. In the feature extraction module, an effective combination of the higher order moments (up to eighth), higher order cumulants (up to eighth) and spectral characteristics are proposed as the efficient features. For classification of the extracted features, ANFIS is investigated as a powerful classifier. In the training of ANFIS, the vector of radius has very important roles for its recognition accuracy. Therefore, in the optimization module, cuckoo optimization algorithm (COA) is proposed for optimization of the classifier to find the optimum value of radius. Experimental results clearly indicate that the proposed hybrid intelligent method has a high classification accuracy to discriminate different types of digital signals even at very low SNRs.