基于智能算法的辐射源信号分选研究

A Study on Radiation Source Signal Sorting Based on Intelligence Algorithm

基于规则和模板的辐射源信号分选算法难以实现对未知辐射源的快速分选;同时,算法对历史数据运用能力不足,模型难以进化,无法适应复杂辐射源信号处理需求。文中研究了一种智能算法辐射源分选方法,设计了在线分选和离线训练分选流程,介绍了监督学习算法对已知辐射源的快速分选和对未知类别辐射源学习的能力,以及非监督学习算法对未知辐射源模糊聚类的能力。该辐射源分选能够实现对辐射源历史数据的挖掘和分析;同时,初步具有对未知类型辐射源分选和识别的能力。

The sorting algorithm of radiation source based on the rule and template can′t realize the sorting of the unknown radiation source signal. Meanwhile the traditional algorithm can′t use historical data effectively or increase with learning, which means the traditional algorithm can′t adapt the need of signal processing in complex radiation source environment. In this paper, the sorting of radiation source based on intelligence algorithm is studied, and the sorting process including online sorting and off-line training is designed. Furthermore, the sorting of known signal and the learning of unknown signal with the supervised learning and the clustering of known signal with unsupervised learning are introduced. The proposed method can use and analyze the historic data effectively and have capability of sorting and recognizing of unknown signal.