In this paper, a distributed approach to radio scene analysis is considered. A Wireless Sensor Network, composed by Software Defined and Cognitive terminals, is used to classify air interfaces present in the radio scene. Two modes, namely Frequency Hopping Code Division Multiple Access and Direct Sequence Code Division Multiple Access, are identified, employing a signal processing technique. Time Frequency analysis, and a distributed decision theory. Advantages given by distributed detection are used to improve the performance of a Mode Identification module. Results in terms of error probability are obtained by modelling the probability density function of considered features as Asymmetric Generalized and Generalized Gaussian functions.