Aircrafts type recognition based on shortwave communication

There is an important military significance about aircrafts type recognition based on shortwave communication. Acoustic signals received by shortwave radio about aircrafts are complex and they contain some valuable information. It is very difficult to identify the aircraft type based on background sound signals of shortwave communication. In order to solve this problem, in this paper two methods for aircrafts type recognition based on shortwave communication are presented. The acoustic signals characteristics of aircrafts are extracted by wavelet packet decomposition (WPD). Support vector machine (SVM) and back propagation (BP) artificial neural network (ANN) as classifiers are adopted to identify five kinds of aircrafts respectively. From results of experiments about classification and recognition of five kinds of aircrafts, the combination of WPD as feature extraction method and SVM as the classifier has better performance and recognition rate than the combination of WPD and BP ANN.