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基于时-空过采样系统的点目标检测性能分析
引用本文:王世涛,张伟,金丽花,侯晴宇.基于时-空过采样系统的点目标检测性能分析[J].红外与毫米波学报,2013,32(1):68-72.
作者姓名:王世涛  张伟  金丽花  侯晴宇
作者单位:1. 哈尔滨工业大学空间光学工程研究中心,黑龙江哈尔滨150001;中国空间技术研究院总体部,北京100094
2. 哈尔滨工业大学空间光学工程研究中心,黑龙江哈尔滨,150001
3. 中国空间技术研究院总体部,北京,100094
基金项目:国家自然科学基金(61007008)
摘    要:为了提高扫描成像系统对于点目标的探测性能,提出了时-空过采样点目标探测体制,并对其进行了目标检测性能分析.首先,分析了单采样体制在点目标探测中易存在跨像元导致的目标能量分散问题,以及探测器随机高强度噪声及空间质子流尖峰信号导致的虚警问题;然后,提出了用于点目标扫描探测的时-空过采样体制.最后,基于图像信噪比对相同光学系统下单采样和时-空过采样系统的目标检测性能进行了比较分析.分析结果表明,通过采样方式能够实现目标能量集中到一个像元,保证了图像信噪比需求.通过高分辨率融合使得目标尺度大干噪声及尖峰的尺度,目标尺度最大扩展至3×3像元,基于目标空间相关的处理可以有效降低了虚警,提升系统检测性能.

关 键 词:扫描成像  时-空过采样  单采样  点目标探测
收稿时间:2012/1/20
修稿时间:2012/2/20 0:00:00

Point target detection based on Temporal-Spatial Over-Sampling system
WANG Shi-Tao,ZHANG Wei,JIN Li-Hua and HOU Qing-Yu.Point target detection based on Temporal-Spatial Over-Sampling system[J].Journal of Infrared and Millimeter Waves,2013,32(1):68-72.
Authors:WANG Shi-Tao  ZHANG Wei  JIN Li-Hua and HOU Qing-Yu
Affiliation:1(1.Research Center for Space Optical Engineering,Harbin Institute of Technology,Harbin 150001,China; 2.Institute of Spacecraft System Engineering,China Academy of Space Technology,Beijing 100094,China)
Abstract:In a traditional scanning imaging system, energy from target is usually weakened by the crossing-pixels phenomenon, and false alarms may happen because of random high intensity noise and peaks in a point target detection. To solve these problems the temporal-spatial over-sampling detection system was proposed. To evaluating its performance, the signal to noise ratio of image obtained by this system was compared with that obtained by single sampling in the same optical system. The results show that the signal to noise ratio can meet the requirement of applications by centralizing the target energy into a pixel in over-sampling system. The target scale can be larger than noise and peaks scale after high-resolution fusion and the target scale can be extended up to 3×3 pixels. Then the false alarm probability can be decreased effectively.
Keywords:scanning imaging  temporal-spatial over-sampling  single sampling  point target detection
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