本项目针对拟建的110米全向可动射电望远镜，开展RFI识别及统计方法研究。首先，依据宽带频谱序列样本，研究常驻干扰信号检测及识别方法，分析信号特征，提取信号特征集，建立常驻干扰信号模板库。其次，搭建瞬态信号检测系统，在电波暗室和现场环境下检测典型瞬态干扰源辐射频谱样本，基于统计学习理论，统计分析瞬态信号特征，研究信号识别及分类算法，建立瞬态信号模块库。另外，依据信号模块库信号特征，调研基于HDF5数据结构的RFI数据存储方法及接口技术，深入分析数据库逻辑存储结构和逻辑数据结构，建立数据查询统计型模型，研究高效数据检索及查询算法，开发基于Web的RFI实时统计分析平台，应用于QTT台址RFI监测站。

This project is to carry out for RFI identification and statistical methods studying, planning to apply with the proposed 110m fully movable radio telescope (QTT, Qi Tai radio telescope). Firstly, the detecting and identifying approaches for resident interference signals are studied based on the wideband spectrum sequence obtained, and the signal feature sets are extracted to further establish signal template library. Secondly, the transient signal detection system is built for typical transient RFI measurement in anechoic chamber and on-site testing environment; what is more, the transient signal characteristics are further statistically analyzed; then the signal recognition and classification algorithms are studied based on the statistical learning theory with the typical transient RFI samples; and the transient interference characteristics are analyzed to further establish Transient signal template library. In addition, RFI data storage method and interface technology are investigated based on the HDF5 data structure and signal characteristics in the signal library built; meanwhile, the logical storage structure and logical data structure of the database are deeply analyzed as well. Additionally, the signal query statistical model is studied for data retrieval and query efficiency, and then a real-time web-based RFI statistical analysis platform is developed to apply with the QTT RFI monitoring station.