| 雷达辐射源模糊识别算法改进 |
| |
| 引用本文： | 李楠,曲长文,苏峰,平殿发.雷达辐射源模糊识别算法改进[J].电子科技大学学报（自然科学版）,2010,39(2):182-185. |
| |
| 作者姓名： | 李楠 曲长文 苏峰 平殿发 |
| |
| 作者单位： | 1.海军航空工程学院 山东 烟台 264001; |
| |
| 基金项目： | 教育部人文社会科学规划项目 |
| |
| 摘 要： | 改进了复杂电磁环境下雷达辐射源模糊识别算法。改进算法通过证据组合对模糊隶属度进行融合，很好地解决了识别中的不确定性，错误的识别结果经过融合后得到去除。采用最优隶属准则进行雷达辐射源类别决策，融合后的辐射源正确识别率得到明显提高。仿真结果及对比实验表明，相比于模糊识别算法，信噪比不小于0dB时，改进算法的正确识别率大于90%。
|
| 关 键 词： | 辐射源识别 证据组合 模糊理论 隶属度 |
| 收稿时间： | 2008-09-03 |
Improved Radar Emitter Fuzzy Identification Algorithm |
| |
| LI Nan,QU Chang-wen,SU Feng,PING Dian-fa.Improved Radar Emitter Fuzzy Identification Algorithm[J].Journal of University of Electronic Science and Technology of China,2010,39(2):182-185. |
| |
| Authors: | LI Nan QU Chang-wen SU Feng PING Dian-fa |
| |
| Affiliation: | 1.Naval Aeronautical and Astronautical University Yantai Shandong 264001;2.Unit 91599 of PLA Laiyang Shandong 265200 |
| |
| Abstract: | Radar emitter identification algorithm based on fuzzy theory is improved. By analyzing fuzzy subordinate values and then using evidence combination principle to combine these values, the recognition uncertainty is solved. The class decision-making is carried out based on optimization subordinate rule, the accurate recognition rate is increased. Simulation experiment shows that new algorithm identification rate more than 90% when SNR higher than 0 dB compared with fuzzy identification method. |
| |
| Keywords: | emitter recognition evidence combination fuzzy theory subordinate |
| 本文献已被 万方数据 等数据库收录！ |
| 点击此处可从《电子科技大学学报（自然科学版）》浏览原始摘要信息 |
|
点击此处可从《电子科技大学学报（自然科学版）》下载全文 |
