基于时空域的暗弱空间运动点目标检测算法

王敏; 赵金宇; 陈涛; 崔博川

doi:10.11999/JEIT161044

基于时空域的暗弱空间运动点目标检测算法

doi: 10.11999/JEIT161044

2.
(中国科学院长春光学精密机械与物理研究所长春 130033) ②(中国科学院大学北京 100049)

基金项目:

国家863计划项目(2011AA8082035)，中国科学院长春光学精密机械与物理研究所三期创新工程资助项目(065X32CN60)

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- 文章访问数: 1603
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- 被引次数: 0
出版历程
- 收稿日期: 2016-10-12
- 修回日期: 2017-02-27
- 刊出日期: 2017-07-19

Moving Point Object Detection from Faint Space Based on Temporal-spatial Domain

2.
(Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China)

Funds:

The National 863 Program of China (2011AA 8082035), The Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, the Third Phase of Innovative Engineering Projects (065X32CN60)

摘要

摘要: 为了对空间目标进行精确定位与跟踪，建立目标运动轨迹，该文对基于运动信息的星图暗弱空间运动点目标检测算法进行研究。首先建立一种新的空间运动点目标描述模型，然后提出基于相关系数矩阵的运动点目标检测算法，最后提取目标运动轨迹，并给出了点目标运动速度的估计模型。根据实测数据和硬件平台，提出了检测概率和虚警率相结合的评价方法对算法进行验证。试验结果表明，所提方法能够在保持较低的虚警概率下获得较高的检测概率，优于参与比较的其它目标检测方法。与单纯扩大望远镜口径相比，该方法为提高空间暗弱目标识别能力提供了具有更高性价比的有效途径。
- 目标检测 /
- 运动点目标 /
- 时空域互相关 /
- 轨迹提取
Abstract: To accurately locate, track space targets, and establish targets trajectory, a study on moving target detection based on motion information for star maps is practiced. Firstly, a new model to characterize the space moving target is constructed, then an algorithm for moving point target detection is proposed based on correlation coefficient matrix statistical information. Based on the detection method, target motion trajectory is finally extracted and the velocity estimation model of the moving target is built. This paper also proposes an evaluation method, which combines detection probability and false alarm probability, to verify this method. The experimental results demonstrate that the proposed method outperforms the compared methods and can achieve high detection probability while keeping low false alarm probability. Compared with simply expanding telescope diameter, this method provides a higher performance-price ratio way to improve the ability of space target detection.
- Target detection /
- Moving point target /
- Temporal-spatial domain correlation /
- Trajectory extraction

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