Identification of Highly Jittered Radar Emitters Signals based on Fuzzy Classification

Emitter signals identification is one of the key procedures in signal processing of ElectronicIntelligence (ELINT). 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 toobtain a complete characterization of clock jitter in microprocessor controlled. To enhance the ability of emitteridentification (EID) to meet the requirement of modern ELINT, a novel identification approach for radar emittersignals based on type-2 fuzzy classifier is presented in this paper. This work discusses the impact of unknownjitter sampling on signal estimation. Based on the ELINT feature extraction of radar emitter signals, the type-2fuzzy classifier is applied to identification of highly jittered radar emitters effectively. Experiment results showsthat the approach can achieve high accurate classification even at higher error deviation level, and has goodcharacteristics of identification.