基于云模型联合几何覆盖算法的雷达信号分选新方法

A Method for Radar Signal Sorting and Recognition Based on Cloud Model and Covering Algorithm

提出了一种基于云模型联合几何覆盖算法的雷达信号分选识别新方法。该方法首先采用几何覆盖算法对具有参数先验信息的雷达信号样本进行学习,将信号划分到不同的覆盖领域,然后用云模型描述各领域与待测脉冲信号之间的隶属度关系,实现待测信号的分选识别,解决当前电子侦察环境中,信号参数交叠的密集雷达信号的实时准确分选问题。仿真结果表明,与传统的信号分选识别方法相比,该方法是有效的。

A new method for radar signal sorting recognition based on cloud model and covering algorithm is proposed. In this method, firstly training for the radar signals with covering algorithm based on prior information, so radar signals are divided into different areas. Then it describes the membership relations between the test pulse signals and areas to achieve signal＇s sorting and recognition. This method solves the problem of radar signals which work in many different ways, and the uncertainty of overlap between different radar characteristic parameters in the current complex electronic environment. The computer simulation results show that, compared with the traditional radar signal sorting recognition, the proposed method is effective.