| 基于改进型CFAR的SAR图像目标检测算法 |
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| 引用本文： | 许剑清,李君宝,马云彤,彭宇.基于改进型CFAR的SAR图像目标检测算法[J].导航定位于授时,2017,4(4):74-81. |
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| 作者姓名： | 许剑清 李君宝 马云彤 彭宇 |
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| 作者单位： | 哈尔滨工业大学自动化测试与控制研究所,哈尔滨,150001 |
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| 基金项目： | 教育部新世纪人才计划，国家自然基金，广西自动检测技术与仪器重点实验室基金 |
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| 摘 要： | 针对传统的双参数恒虚警率(Constant False Alarm Rate,CFAR)算法存在的虚警率高、实现过程繁琐、算法执行效率低等问题,提出了一种改进型的CFAR检测算法。该算法根据SAR图像的统计直方图,对可疑的目标像素进行预筛选,再用2个滑动窗口对像素进行判别。改进型的CFAR检测算法简化了原检测算法的结构,降低了检测结果的虚警率,提高了算法的计算效率,并在国际公开的雷达数据集上进行软件与DSP硬件的应用验证,测试表明该算法的有效性。
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| 关 键 词： | 合成孔径雷达 SAR图像 目标检测 恒虚警率 DSP |
SAR Image Target Detection Algorithm Based
on Improved CFAR |
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| XU Jian-qing,LI Jun-bao,MA Yun-tong and PENG Yu.SAR Image Target Detection Algorithm Based
on Improved CFAR[J].Navigation Positioning & Timing,2017,4(4):74-81. |
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| Authors: | XU Jian-qing LI Jun-bao MA Yun-tong and PENG Yu |
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| Institution: | Automatic Test and Control Institute, Harbin Institute of Technology, Harbin 150001, China,Automatic Test and Control Institute, Harbin Institute of Technology, Harbin 150001, China,Automatic Test and Control Institute, Harbin Institute of Technology, Harbin 150001, China and Automatic Test and Control Institute, Harbin Institute of Technology, Harbin 150001, China |
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| Abstract: | The traditional CFAR algorithm
has the disadvantages of
high false alarm rate, low efficiency, cumbersome realization process, etc. In order to solve the above problems, an improved CFAR detection algorithm is proposed. According to the statistical histogram of the SAR images, the proposed algorithm
can perform pre-screening for suspected target pixels. Then the detected pixels are distinguished by two sliding windows. The improved CFAR detection algorithm simplifies the structure of the traditional detection algorithm. At the same time, it reduces the false alarm rate and improves the efficiency of the algorithm. Experiments based on the international public radar data-sets for application verification are done on software and DSP platform respectively, which show effectiveness of the proposed algorithm |
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