ICNPAA 2010: Mathematical Problems in
Engineering, Aerospace and Sciences

In this article, a new effort is done to decrease the emitter identification (EID) procedure based on a multilayer vector neural network (VNN) and Fuzzy Logic via a supervised learning algorithm along with more comprehensive input parameters of the received signal in a real-time manner. As a matter of fact, we define a new Pulse Descriptor Word (PDW) used for modern RWRs (Radar Warning Receivers) and provide the signal recognition pattern using simultaneously processing parameters encompassing Career Frequency (CF), Pulse Repetition Frequency (PRF), Pulse-Width (PW), Pulse Amplitude (PA), Angle of Arrival (AOA), Transmitter Power (TP) and Antenna Scan Rate (ASC). The input parameters are ranked via applicable values so as to prioritize the learning algorithm of the VNN; consequently, the processing time would decrease to a certain extent compared to the same approaches and more reliable results in coping with the problem of multi-threat’s ambiguity are gained.