Deep learning in electronic warfare systems: Automatic intra-pulse modulation recognition
Date
2018
Editor(s)
Advisor
Supervisor
Co-Advisor
Co-Supervisor
Instructor
Source Title
2018 26th Signal Processing and Communications Applications Conference (SIU)
Print ISSN
Electronic ISSN
Publisher
Institute of Electrical and Electronics Engineers
Volume
Issue
Pages
Language
Turkish
Type
Journal Title
Journal ISSN
Volume Title
Series
Abstract
Detection and classification of radars in electronic warfare systems is a major problem. In this work, we propose a novel deep learning based method that automatically recognizes intra-pulse modulation types of radar signals. We use reassigned short-time Fourier transforms of measured signals and detected outliers of the phase differences using robust least squares to train a hybrid structured convolutional neural network to distinguish frequency and phase modulated signals. Simulation results show that the developed method highly outperforms the current state-of-the-art methods in the literature.