| 基于图像处理技术自动判别雷达异常产品 |
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| 引用本文： | 邵楠,裴翀,刘传才,周薇,张乐坚,李巍.基于图像处理技术自动判别雷达异常产品[J].气象科技,2013,41(6):993-997. |
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| 作者姓名： | 邵楠 裴翀 刘传才 周薇 张乐坚 李巍 |
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| 作者单位： | 中国气象局气象探测中心，北京 100081;中国气象局气象探测中心，北京 100081;南京理工大学,南京 210094;中国气象局气象探测中心，北京 100081;中国气象局气象探测中心，北京 100081;中国气象局气象探测中心，北京 100081 |
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| 基金项目： | 中国气象局气象灾害监测预警与应急工程项目资助 |
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| 摘 要： | 对雷达产品的实时监控是中国气象局气象探测中心运行监控实时业务工作的重要内容之一，因此实现自动化识别雷达异常产品具有重要的现实意义和研究价值。论述基于图像处理技术实现自动识别雷达异常产品，详细介绍系统实现模型及雷达数据异常自动识别算法，其中主要阐述了特征提取、迭代学习器等相关内容。通过对检测出的雷达产品异常产品分析表明，基于图像处理技术的雷达产品异常自动识别系统可以高效的、实时的检测出异常雷达产品，便于技术人员快速发现雷达异常并及时修复，也可作为雷达维修或雷达升级改造的依据，提高雷达的使用效率。
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| 关 键 词： | 雷达异常回波 特征提取 迭代学习器 |
| 收稿时间： | 2012/10/11 0:00:00 |
| 修稿时间： | 2012/10/19 0:00:00 |
Automatic Identification System of Abnormal Radar Echoes Based on Image Processing Technology |
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| Shao Nan,Pei Chong,Liu Chuancai,Zhou Wei,Zhang Lejian and Li Wei.Automatic Identification System of Abnormal Radar Echoes Based on Image Processing Technology[J].Meteorological Science and Technology,2013,41(6):993-997. |
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| Authors: | Shao Nan Pei Chong Liu Chuancai Zhou Wei Zhang Lejian and Li Wei |
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| Institution: | 1 (1 CMA Meteorological Observation Centre, Beijing 100081; 2 Nanjing University of Science Technology, Nanjing 210094 ) |
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| Abstract: | The real time monitoring of radar products is an important part of real time running and monitoring services in the CMA Meteorological Observation Centre, and the automated identification of abnormal radar products will therefore have practical significance and research value. The identification system based on image processing technology to achieve the automatic recognition of abnormal radar products is discussed, and the system model and automatic recognition algorithm of radar data abnormity are introduced in detail, aiming at the feature extraction, iterative learning, and so on. The analysis of the detected radar product abnormalities shows that the automatic identification system based on image processing technology can detect abnormal radar products efficiently in real time to facilitate the quick location of abnormal radar and timely repair, and can also be used as a basis for radar repair or for radar upgrading to improve the efficiency of radar applications. |
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| Keywords: | radar echo feature extraction iterative learning |
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