Automatic intra-pulse modulation recognition using support vector machines and genetic algorithm
Jie Li, Ge Zhang, Yang Sun, Erlei Yang, Lede Qiu, Wei Ma · 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC) · 2017
A new method, based on support vector machines (SVMs) and genetic algorithm (GA), is proposed for automatic Intra-Pulse modulation recognition (AIMR). In particular, the best feature subset from the combined pulse descriptor word (PDW) feature set and time-frequency feature set is optimized using genetic algorithm. Compared to the conventional decision-theoretic method, the method proposed avoids the frequency ambiguity caused by signal noise. Simulation results show that this method is more robust and effective than other existing approaches, particularly at a low signal noise ratio (SNR).