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空间目标探测与识别方法研究
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摘要
随着人类对空间技术开发利用的规模不断扩大,空间日益成为维护国家安全的“战略高地”,空间产业也逐渐成为促进国民经济发展的重要支柱。其中,空间目标的探测、识别与跟踪技术的发展显得尤其活跃。空间目标探测与识别系统的主要任务是对重要空间目标进行精确探测和跟踪,确定可能对航天系统构成威胁的空间物体的任务、尺寸、形状和轨道参数等重要目标特性,对目标特性数据进行归类和分发。空间目标主要指卫星,包括工作的卫星和不工作的卫星,同时也包括空间碎片,如进入空间轨道的助推火箭、保护罩和其他物体,还包括进入地球外层空间的各种宇宙飞行物,如彗星和小行星。
     传统的空间目标探测多采用地基光学望远镜、雷达探测器和无线电信号探测器组成的监视网,对空间目标进行探测和跟踪。这种探测方式的优点是技术较成熟、投资成本低,能够对空间目标进行有效地搜索和跟踪,但也容易受到气象、地理位置和时间的限制,使得小目标以及目标细节的观测受到影响。
     为了克服地基空间目标探测系统的各种缺点,各航天大国开展了天基空间目标探测技术的开发和应用。天基空间目标探测通过将各种探测器送入太空环境的方式对空间目标进行探测。该探测方式克服了地基空间目标探测的缺点,可以避免大气对观测效果的影响,同时也避免了地理位置和时间的限制,能够得到更好的探测结果。
     目前,天基空间目标探测有多种探测方式,这些探测方式都有各自的优缺点,单个探测器或单种探测方式所获得的单一信息已经难以达到探测要求。
     为了克服在天基空间目标探测中使用单个传感器或单种探测方式的缺陷,本论文在全面总结国内外天基空间目标探测与识别领域发展现状的基础上,进行了天基空间目标探测与识别的多载荷融合技术研究。首先,针对太空环境的特殊背景以及单载荷探测的局限性,提出了基于红外和可见光的天基空间目标多载荷融合方案,分解了方案中的关键技术,并对部分关键技术进行了研究。然后,在此基础上开展了可见光和红外两类观测载荷的多载荷图像处理与识别技术研究,针对远距离、近距离两个典型的阶段,分别提出了天基空间目标探测的多载荷融合技术与方法;采用了双目测距法对近距离目标进行定位技术研究;最后,搭建了功能验证平台对所提出的多载荷融合技术进行仿真与验证。该平台已经具备了实验演示和拓展的技术基础和要求,为天基空间目标探测与识别多载荷融合技术的进一步研究奠定基础。
As the development scale of space technology used by human expand, the space has increasingly become a "strategy heights" of protecting national security, and the space industry also become an important pillar of national economic development. In particular, the space target detection, identification and tracking technology is active. The main task of space target detection and identification system is to detect and track the importance space target accurately, which is in order to determine whether the space target is a threat for national space system. If a space target is determined as a threat, the next step is to get the importance characteristic information about it:task, size, shape, the orbit parameter, and etc al. Finally, the data about the target characteristics will be classified and distributed. The space target include work satellite, doesn't work satellite and space debris. The space debris includes the booster rocket, shields, and other objects into space orbit, and also includes comets and asteroids.
     In traditional, the space target detection mainly rely on the ground-based detect net which is consist of ground-based optical telescopes, radar detectors, and radio signal detectors. The advantage of ground-based detect method include more mature technology, lower investment, and effective search and track capacity. But it can be easily constrained by weather, location and time, which will affect the detection result for small target and its details.
     In order to overcome the shortcomings of ground-based space target detect system, the space powers carry out the space-based space target detect technology development and applications. Space-based space target detect system can detect the objectives by sending the space target detector into space, this detection method can avoid the effect of atmosphere on the observations, and also avoid the location and time constraints, can get better detection results.
     Currently, space-based space target detection include a variety of detection methods, these detection method have their own advantages and disadvantages, the information obtained from a single detector or single-species detection method is limited, can't satisfy modern detection need.
     In order to avoid the defect of the space-based space target detection using a single sensor or single species detection method, based on comprehensively summarizing the status of domestic and international developments in the field of Space-based space target detection and identification, this paper is about the research of the Space-based Space Target detection and identification technology using multi-sensor. Due to the special background of space environment and the limitation of the single-sensor detection, the multi-sensor fusion program for the infrared and visible Space-based space target is proposed with each individual sensor design parameter in the research, and this paper also analysis the key technology. On the basis of this research, our seminar investigates the multi-sensor image processing and identifying technology with two types of observation sensor:the infrared and visible; For the two typical sections:long distance and close distance, we propose respectively the method and technique of the multi-sensor fusion for the Space-based Space Target Detection; We also adopt to the method of binocular distance measurement to analysis targeting technology for the close target; At last, we build up a verification platform to simulate and verify the proposed multi-sensor fusion technique. With the effort of our seminar, the simulation platform has met the further demand for experimental demonstration.
引文
[1]乔凯,王治乐,丛明煜.空间目标天基与地基监视系统对比分析[J].光学技术.2006,32(5).744--749.
    [2]周彦平,舒锐,陶坤宇等.空间目标光电探测与识别技术的研究[J].光学技术.2007,33(1):68-73.
    [3]陈罗婧,崔玉福,李劲东.国外天基空间目标监视系统研究现状及进展[J].中国空间科学学会空间机电与空间光学专业委员会2008年学术年会.18-23.
    [4]张景旭.国外地基光电系统空间目标探测的进展[J].中国光学与应用光学.2009,2(1):10-16.
    [5]李东源.国外的地基对空间目标光电探测系统浅析[J].光电对抗与无源干扰.2003,69(1):9-11.
    [6]王杰娟,于小红.国外天基空间目标监视研究现状与特点分析[J].装备指挥技术学院学报.2006,17(4):33-37.
    [7]李颖,张占月,方秀花.空间目标监视系统发展现状及展望[J].国际太空.2004,(6):28-31.
    [8]Stair, A. T., Jr. Mill, J.D.The Midcourse Space Experiment (MSX) [C]. IEEE international conference on Aerospace.1997:233-235.
    [9]stokes G. H.,von Braun C.,Sridharan R.,and et al.The space-based visible program.Lincoln Laboratory Journal.1998,11(2):205~238.
    [10]Jayant Sharma,Grant H.Stokes,Curt von Braun,and et al.Toward operational space-based space surveillance.Lincoln Laboratory Journal.2002,13(2): 309~334.
    [11]周海银,潘晓刚,李董辉.基于天基空间目标监视系统的定轨技术研究[J].系统仿真学报.2008,20(13):3538-3547.
    [12]谭莹.天基空间目标探测技术探讨[J].空间电子技术.2006,(3):5-8.
    [13]吕杰,吴季,孙波.天基雷达观测空间碎片的研究现状及关键技术分析[J].航天返回与遥感.2003,24(4):28-33.
    [14]张慧娟,梁彦,程咏梅等.运动弱小目标先跟踪后检测技术的研究进展[J].红外技术.2006,28(7):423-429.
    [15]I. S. Reed, R. M. Gagliardi, H. M. Shao.Application of three-demensional filtering to moving target detection[J].IEEE Transactions on Aerospace and Electronic System(AES).1983:898~905.
    [16]I. S. Reed, R. M. Gagliardi, L. Stotts.Optical moving target detection with 3-D matched filtering[J].IEEE Transactions on Aerospace and Electronic System (AES).1988,24(4):327~336.
    [17]S. D. Blostein, T. S. Huang.Detecting small moving objects in image sequences using sequential hypothesis testing[J].IEEE Transactions on Signal Processing.1991,39(7):1611~1629.
    [18]强勇,焦李成,保铮.一种有效的用于雷达弱目标检测的算法[J].电子学报.2003,31(3):440-443.
    [19]R. Liou, M. R. Azimi-Sadjadi. Dim target detection using high order correlation method[J].IEEE Transactions on Aerospace and Electronic System (AES).1993,29(3):841~856.
    [20]R. Liou, M. R. Azimi-sadjadi.Multiple target detection and track identification using modified high order correlations[A].IEEE Proceedings of ICNN'94,Orlando[C].1994:3277~3282.
    [21]R. Liou, M. R. Azimi-Sadjadi.Multiple target detection using modified high order correlations[J].IEEE Trans.on AES.1998,34(2):553~567.
    [22]Haritaoglu I.,Harwood David,Davis L. S..Real-time surveillance of people and their activities[J].IEEE Transaction on Pattern Analysis and Machine Intelligenc.2000,22(8).
    [23]Tekalpa M.Digital video processing[M].Prentice-Hall,1995.
    [24]朱克忠.基于光流法对移动目标的视频检测与应用研究[硕士学位论文].安徽.合肥工业大学.1-7.
    [25]杨威,张田文.复杂景物环境下运动目标检测的新方法[J].计算机研究与发展.1998,35(8):724-728.
    [26]马奔,史忠科,皮燕妮.成像目标跟踪算法分析[J].西安电子科技大学学报(自然科学版).2005,32(2):477-480.
    [27]扬大为,王淡.基于双差分法的目标检测与分析[J].沈阳工业学院.2004,23(2):27-30.
    [28]Gary Bradski, Adrian Kaehler编著.于仕琪,刘瑞祯译.学习OpenCV中文版).北京:清华大学出版社.2009.10.
    [29]雷鸣,张广军.一种新颖的抗旋转快速图像匹配算法[J].光电子激光.2009,20(3):397-401.
    [30]陶晓勋.基于特征的快速抗旋转图像匹配方法研究[硕士学位论文].江苏.河海大学.30-36.
    [31]ZOU wei-jun, BO Yu-ming, CHEN Yi. Windows-tracking technology for an electro-optical tracking and pointing platform[J]. 红外与激光工程.2008, 37(4):602~606.
    [32]王阿妮.基于红外与可见光的多源传感器协同检测与跟踪技术研究[硕士学位论文].西安.中国科学院西安光学精密机械研究所.52-58.
    [33]吴晓阳.基于OpenCV的运动目标检测与跟踪[硕士学位论文].浙江.浙江大学.2008:60-61.
    [34]Shinichiro Omachi,Masako Omachi.Fast Template Matching With Polynomials[J].IEEE Trans. on Image Processing.2007,16(8):2139-2149.
    [35]定宇.天基目标跟踪与识别[硕士学位论文].黑龙江.哈尔滨工程大学.2007:59-60.
    [36]董士崇,王天珍,许刚.视频图像中的运动检测[J].武汉理工大学学报(信息与管理工程版).2004,26(4).
    [37]WAKD L. Some terms of reference in data fusion [J]. IEEE Transactions on Geoscience and Remote Sensing.1999,37(3):1190~1193.
    [38]夏成革,何友.多传感器图像融合综述[J].电光与控制.2002.4(9):4
    [39]韩思奇,王蕾.图像分割的阈值法综述[J].系统工程与电子技术.2002,24(6):91-94.
    [40]李阳.基于视觉的移动机器人运动目标跟踪技术研究[硕士学位论文].北京.北京交通大学.36.
    [41]冯少荣,肖文俊.基于样本选取的决策树改进算法[J].西南交通大学学报.2009,44(5):643-647.
    [42]朱大奇,史慧.人工神经网络原理及应用[M].北京:科学出版社,2006.
    [43]刘艳丽.随机森林综述[硕士学位论文].天津.南开大学.1-5.
    [44]Zhang Zhengyou.A Flexible New Technique for Camera Calibration[J].IEEE Trans. on Pattern Analysis and Machine intelligence.2000,22(11):1330~1334.
    [45]http://www.vision.caltech.edu/bouguetj/calib_doc/

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