空中弱目标天基光学探测性能表征及匹配设计方法
投稿时间:2019-03-06  修订日期:2019-04-10  点此下载全文
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作者单位E-mail
乔凯 北京跟踪与通信技术研究所 qk_lucky@sohu.com 
智喜洋 哈尔滨工业大学 空间光学工程研究中心 zhixiyang@hit.edu.cn 
杨冬 北京空间飞行器总体设计部  
巩晋南 哈尔滨工业大学 空间光学工程研究中心  
胡建明 哈尔滨工业大学 空间光学工程研究中心 hjm1007491571@163.com 
基金项目:国家自然科学基金(61605035)
中文摘要:针对远距离空中弱目标光学探测的需求,提出天基探测系统性能表征与关键指标匹配设计方法。首先立足于天基光学探测全链路,分析得出影响天基观测条件下空中复杂环境背景中弱目标光学探测的主要因素,包括场景杂波、探测系统的光谱辐射尺度、几何尺度等;然后对上述影响因素进行表征建模,建立目标的图像信噪比与影响要素之间的关系模型,即探测系统性能表征模型;最后以典型探测场景为例,通过研究目标在不同场景杂波及探测多尺度耦合特性下的信噪比变化规律,提出探测谱段优选及其与空间分辨率的匹配设计建议,可为我国天基探测系统设计、指标论证、信息处理算法优化提供理论依据与科学指导。
中文关键词:空中弱目标  天基探测  探测性能表征模型  谱段优选  匹配设计
 
Performance characterization and matching design method of space-based optical detection for weak aerial target
Abstract:Aiming for long-distance optical detection of weak aerial targets, we in this paper propose a method of performance characterization and key indexes matching design for a space-based detection system. Firstly, we analyze the main factors that affect the optical detectability of weak targets under complex environment based on the full link of the space-based detection system, including scene clutter, spectral radiation scale and geometric scale of detection system, etc. We then combine the above influencing factors to establish a performance characterization model which represents the relationship between the image signal-to-noise ratio of target and the above-mentioned influencing factors, that is, the performance representation model of the detection system. Finally, taking a typical detection scene as an example, by studying signal-to-noise ratio of target under different scene clutter and multi-scale coupling characteristics, the optimization of detection spectrum and its matching design with spatial resolution are proposed, which can provide theoretical basis and scientific guidance for the design of the space-based detection system, demonstration of system indexes and optimization of information processing algorithms.
keywords:Weak aerial target  Space-based detection  Characterization model of detection performance  Spectral optimal selection  Matching design
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