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: 1510
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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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参考文献(28)

吴连大. 人造卫星与空间碎片的轨迹和探测[M]. 北京: 中国科学技术出版社, 2011: 1-8.

WU Lianda. Orbits and Detection of Satellite and Space Debris[M]. Beijing: China Science and Technology Press, 2011: 1-8.

孙挺, 齐迎春, 耿国华. 基于帧间差分和背景差分的运动目标检测算法[J]. 吉林大学学报(工学版), 2016, 46(4): 1325-1329. doi: 10.13229/j.cnki. jdxbgxb201604044.

SUN Ting, QI Yingchun, and GENG Guohua. Moving object detection algorithm based on frame difference and background subtraction[J]. Journal of Jilin University (Engineering and Technology Edition), 2016, 46(4): 1325-1329. doi: 10.13229/j.cnki.jdxbgxb201604044.

江汉红, 熊玮佳, 李庆. 一种基于GMM的目标检测改进算法[J]. 武汉理工大学学报, 2013, 35(3): 132-135. doi: 10.3963 /j.issn.1671-4431.2013.03.027.

JIANG Hanhong, XIONG Weijia, and LI Qing. An improved target detection algorithm based on GMM[J]. Journal of Wuhan University of Technology, 2013, 35(3): 132-135. doi: 10.3963/j.issn.1671-4431.2013.03.027.

PICCARDI M. Background subtraction techniques: A review [C]. IEEE International Conference on Systerms, Man and Cybemeties, Sydney, Australia, 2004: 3099-3104. doi: 10.1109 /ICSMC.2004.1400815.

VALLEJO D, ALBUSAC J, and JIMENEZ L. A cognitive surveillance system for detection incorrect traffic behaviors[J]. Expert Systems with Applications, 2009, 36(7): 10503-10511. doi: 10.1016/j.eswa.20 09.01.034.

SENET T, EISELEIN V, and PATZOLD M. Efficient real- time local optical flow estimation by means of integral projections[C]. International Conference on Image Processing (ICIP 2011), Brussel, 2011: 2393-2396. doi: 10.1109/ICIP. 2011.6116111.

肖军, 朱世鹏, 黄杭, 等. 基于光流法的运动目标检测与跟踪算法[J]. 东北大学学报(自然科学版), 2016, 37(6): 770-774. doi: 10.3969/j.issn.1005-3026.2016.06.003.

XIAO Jun, ZHU Shipeng, HUANG Hang, et al. Object detecting and tracking algorithm based on optic flow[J]. Journal of Northeastern University (Natural Science), 2016, 37(6): 770-774. doi: 10.3969/j.issn.1005-3026.2016.06.003.

KRAVCHONOK A. Detection of moving objects in video sequences by the computation of optical flow based on region growing[J]. Pattern Recognition and Image Analysis, 2011, 21(2): 283-286. doi: 10.1134/S1054661811020647.

刘洪彬, 常发亮. 权重系数自适应光流法运动目标检测[J]. 光学精密工程, 2016, 24(2): 460-468. doi: 10.3788/OPE. 20162402.0460.

LIU Hongbin and CHANG Faliang. Moving object detection by optical flow method based on adaptive weight coefficient [J]. Optics and Precision Engineering, 2016, 24(2): 460-468. doi: 10.3788/OPE.20162402.0460.

李淼, 龙云利, 李骏, 等. 采用多伯努利滤波器的过采样点目标检测前跟踪[J]. 光学精密工程, 2015, 23(12): 3446-3455. doi: 10.3788/OPE.20152312.3446.

LI Miao, LONG Yunli, LI Jun, et al. Oversampling point target track-before-detect by Multi-Bernoulli filter[J]. Optics and Precision Engineering, 2015, 23(12): 3446-3455. doi: 10.3788/OPE.20152312.3446.

ZHENG D K, WANG S Y, and QIN X. A dynamic programming track-before-detect algorithm based on local linearization for non-Gaussian clutter background[J]. Chinese Journal of Electronics, 2016, 25(3): 583-590. doi: 10.1049/cie. 2016.05.027.

DAVEY S J, RUTTEN M G, and CHEUNG B. A comparison of detection performance for several track-before-detect algorithms[C]. Proceedings of the IEEE 2008 International Conference on Information Fusion, Cologne, Germany, 2008, 2008: 1-8. doi: 10.1155/2008/428036.

李振伟, 张涛, 孙明国. 星空背景下空间目标的快速识别与精密跟踪[J]. 光学精密工程, 2015, 23(2): 589-599. doi: 10.3788 /OPE.20152302.0589.

LI Zhenwei, ZHANG Tao, and SUN Mingguo. Fast recognition and precise orientation of space objects in star background[J]. Optics and Precision Engineering, 2015, 23(2): 589-599. doi: 10.3788/OPE.20152302.0589.

张健, 娄树理, 任建存. 基于时序多帧投影的空间目标检测算法[J]. 激光与红外, 2015, 45(1): 88-93. doi: 10.3969/j.issn. 1001-5078.2015.01.020.

ZHANG Jian, LOU Shuli, and REN Jiancun. Space target detection algorithm based on sequential multi-frames projection[J]. Laser Infrared, 2015, 45(1): 88-93. doi: 10.3969/j.issn.1001-507.2015.01.020.

王恩旺, 王恩达. 改进的帧差法在空间运动目标检测中的应用[J]. 天文研究与技术, 2016, 13(3): 333-339. doi: 10.14005/ j.cnki.issn1672-7673.20160316.00.

WANG Enwang and WANG Enda. Application of an improved frame difference method in space moving target detection[J]. Astronomical Research and Technology, 2016, 13(3): 333-339. doi: 10.14005/j.cnki.issn1672-7673.20160316. 002.

黄宗福, 汪金真, 陈曾平. 光电探测中空间目标和恒星目标运动特性分析[J]. 光电工程, 2012, 39(4): 67-72. doi: 10.3969 /j.issn.1003-501X.2012.04.012.

HUANG Zongfu, WANG Jinzhen, and CHEN Zengping. Motion characteristic analysis of space target and stellar target in opto-electronic observation[J]. Opto-Electronic Engineering, 2012, 39(4): 67-72. doi: 10.3969/j.issn.1003- 501X.2012.04.012.

张春华, 周晓东, 陈维真. 基于背景抑制的星空图像目标运动轨迹提取[J]. 红外与激光工程, 2008, 37(1): 143-146. doi: 10.3969/j.issn.1007-2276.2008.01.033.

ZHANG Chunhua, ZHOU Xiaodong, and CHEN Weizhen. Target trace acquisition method of star images based on background elimination[J]. Infrared and Laser Engineering, 2008, 37(1): 143-146. doi: 10.3969/j. issn.1007-2276.2008.01. 033.

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