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Detection method for small and dim targets from a time series of images observed by a space-based optical detection system

机译:从天基光学检测系统观察到的时间序列图像中的小目标和暗目标的检测方法

摘要

To revisit cataloged space targets, a space-based optical detection system normally observes space targets continuously in a target tracking mode. In the time series of images produced by continuous observation, there are not only the target but also complicated background clutter (a mass of stars) and noises. The existing method only can detect the target with an signal-to-noise ratio (SNR) greater than 6 from these images. This paper presents a detection method for the target with an SNR less than 6. The proposed method consists of an SNR enhancement algorithm and an adaptive background and noise suppression algorithm. Simulation and analytical results show the proposed method detects the target submerged in noise and background clutter when SNR is equal to 3 and the detection probability and the false alarm probability both reach very high performance. This proposed method can help solve the problem of revisiting some weak cataloged space targets.
机译:为了重新访问分类的空间目标,天基光学检测系统通常以目标跟踪模式连续观察空间目标。在连续观察产生的图像时间序列中,不仅存在目标,而且还存在复杂的背景杂波(大量星星)和噪声。现有方法只能从这些图像中检测出信噪比(SNR)大于6的目标。提出了一种信噪比小于6的目标检测方法。该方法由信噪比增强算法和自适应背景噪声抑制算法组成。仿真和分析结果表明,该方法能够在信噪比等于3时检测到淹没在噪声和背景杂波中的目标,并且检测概率和虚警概率均达到很高的性能。所提出的方法可以帮助解决重新访问一些弱分类目录目标的问题。

著录项

  • 作者

    Pan HB; Song GH; Xie LJ; Zhao Y;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 入库时间 2022-08-20 20:56:17

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