Classifying Models And Algorithms For Communication Signals In Complex Electromagnetic Environment

Signal modulation recognition play an important role in electronic warfare, electronic countermeasures an important prerequisite for the enemy only pre-detected signal radiation source, in order to effectively imposed interference. Currently, a variety of military and civilian radar, radio extensive use complicated electromagnetic environment. How can extract and identify useful signal in such dense, complex, changing signal environment, become a major problem for people.The main difficulty is:1, Electronic surveillance equipment involving military secrets, it is difficult to find papers about this aspect.After a long period of research, the focus of most of the papers are academic discussion, refer to military purposes almost no;2, The scalability of the system. The pre-made pre-research work, is just for the individual signal modulation recognition, later, the focus is on more signals modulation recognition, need to be considered expansion on the basis of the original system3Give a model of the signal modulation recognition system. Needless to say, a good model will greatly shorten the systems engineering implementation cycle, and take a cost savings, but also better in actual combat effective.The paper focuses on the above-mentioned problems, mainly done this following works:(1) Took a large number of the research work on electronic surveillance equipment, and discussed with field engineers, gained invaluable advice;(2) Researched a complete set of signal modulation recognition approach, which is great guiding significance for the later stages of the system expansion;(3) Mixed different signal-to-noise ratio of the noise for enhancing the complexity of electromagnetic environment, made it close to the complicated electromagnetic environment.(4) Took fuzzy kernel clustering means analysis parameters of the signal characteristics, obtained a very good separation efficiency...