Emitter identification of electronic intelligence system using type-2 fuzzy classifier

Abstract

Emitter signal recognition is one of the key procedures in signal processing of electronic intelligence (ELINT). In particular, the identification of radar emitters has been important with the advances in radio frequency, electronics and control technologies. Jitter is an unintentional form of modulation that can have a wide variety of sources. Timing-related data errors will occur if jitter is beyond acceptable limits. Designers need a fast and easy way to obtain a complete characterization of clock jitter in the microprocessor controlled. To enhance the ability of specific emitter identification (SEI) to meet the requirement of modern ELINT, a novel identification approach for radar emitter signals based on type-2 fuzzy classifier is presented in this paper. In fuzzy type-2 sets, the uncertainty is represented as an extra dimension. In this article, we show how it is possible to reduce the effect of SEI-induced highly jittered radar emitters in ELINT, with the classifiers of type-1 and type-2 fuzzy logic. This work discusses the impact of unknown jitter sampling on signal estimation. Based on the ELINT feature extraction of radar emitter signals, the type-2 fuzzy classifier is applied to identification of radar emitters effectively. Experiment results shows that the approach can achieve high accurate classification even at higher error deviation level and has good characteristics of identification.