时频重叠信号脉内特征提取与协同分选

项目名称： 时频重叠信号脉内特征提取与协同分选

项目编号： No.61201287

项目类型： 青年科学基金项目

立项/批准年度： 2013

项目学科： 电子学与信息系统

项目作者： 李林

作者单位： 西安电子科技大学

项目金额： 26万元

中文摘要： 雷达信号分选是电子侦察信号处理的关键环节，直接决定电子侦察设备的性能并影响电子对抗系统的控制与决策。当前雷达信号分选面临着脉冲密度大、环境复杂、雷达参数多变等困难，导致截获的脉冲信号时频重叠情况严重，常规分选方法很难凑效。本项目针对时频重叠信号，重点研究基于高阶时频分析的脉内特征提取和基于电子侦察平台组网的信号协同分选算法。主要研究内容包括：(1) 研究高阶时频分布统一数学模型；(2) 研究时频重叠信号的脉内特征提取与特征融合算法；(3) 设计ELINT、ESM和RWR等雷达侦察平台的组网框架，实现数据级和特征级信息融合；(4) 研究基于盲源分离的时频重叠信号协同分选，及信号多径抑制算法。通过开展仿真实验和基于实测数据的验证评估，提高复杂电磁环境下时频重叠信号特征提取与协同分选的有效性、可靠性和实时性，为时频重叠信号分选的工程化应用提供理论和技术支撑。

中文关键词： 电子侦察；信号分选；脉内特征；时频重叠信号；时频分布

英文摘要： Radar signal deinterleaving is a crucial technique in signal processing of electronic intelligence, which directly determines the performance of electronic reconnaissance devices and the control and decision of electronic contermeasure system. Right now, signal deinterleaving faces with the difficultis including high signal density, complex environment, variable radar parameter, etc. These problems result in serious time-frequency overlaping of the intercepted pulse signals and ineffectiveness of the conventional deinterleaving methods. This project mainly deals with studies higher-order time-frequency distribution based intra-pulse feature extraction and electronic reconnaissance network based cooperating deinterleaving for time-frequency overlaped signals. The main contents include: (1) Research the unified model of higher-order time-frequency distribution including ambiguity function, time-frequency analysis, cyclic spectrum, etc. (2) Reasearch the intra-pulse feature extraction algorithms and the feature fusion methods for time-frequency overlaped signals. (3) Design the network scheme of radar reconnaissance platforms including ELINT, ESM , RWR, etc., implement information fusion both in data level and feature level. (4) Research signal cooperating deinterleaving based on blind source separation, and signal

英文关键词： electronic reconnaissance；signal deinterleaving；intra-pulse feature；time-frequency overlaped signal；time-frequency distribution