| 摘要: |
| 本文在研究带偏差单元内部回归神经网络（Internally Recurrent Net，IRN）算法的基础上，分析了雷达特征参数和雷达威胁类型的内在联系；利用统计分析和特征建模的方法获取先验知识、设计分类器并求取模糊隶属函数，结合IRN自学习特性和模糊隶属函数的分类功能识别出目标雷达辐射源可能的威胁类型，给出识别可信度。 |
| 关键词: 雷达电子对抗 神经网络 辐射源识别 特征提取 特征分析与建模 知识库 |
| DOI：10.3969/j.issn.1001-893X. |
| 投稿时间：2005-03-10 |
| 基金项目: |
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| An Algorithm for Radar Emitter Recognition Based on Internally Recurrent Net |
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| Abstract: |
| A radar emitter recognition algorithm based on Internally Recurrent Net (IRN)is presented .The latency incidence relation of radar parameters and radar threat type is studied.Statistic analysis and feature modeling techniques are used to conclude apriority knowledge and induce classifiers and fuzzy subjection functions. Considering radars' multi-feature characteristics, the algorithm integrates the classifying function of fuzzy subjection function and fast convergence characteristic of IRN to output expectation threat type and its reliability. |
| Key words: Radar ECM,Neural network,Emitter recognition,Feature extraction,Feature analysis & modeling,Knowledge database |
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