The application and improvement of Grey associated analysis theory in Radar Emitter Source signal´s sorting and Identification

Radar Emitter Source signal´s sorting and identification is an important problem for the electronic countermeasure processing. Grey associated analysis theory is a effective method for pattern sorting and recognition. But the traditional Grey associated analysis theory has a key problem, which is how to decide the feature associated weight. So, in the thesis, directing at the characteristics of imperfection and vagueness of Radar Emitter Source signal information acquired by electronic equipment in complex electromagnetic environment, based on the traditional Grey associated analysis theory, an improved Grey associated analysis theory is provided. First, the traditional Grey associated analysis theory is show in detail and describes the problem of feature associated weight´s decision. Secondly, on the basis of Shannon information entropy theory, the weight of feature associated weight is computed in real time. Finally, a simulation experiment is designed to check the result. According to the simulation experiment, the new grey associated analysis theory has higher objective identification rate, better adaptability and stronger computation reliability.