用户名: 密码: 验证码:
红外单站被动定位技术研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着现代军事技术的迅速发展,光电对抗技术在现代战争中也获得了迅速的发展和广泛的应用,其中高价值机动平台(如战略轰炸机、预警机、洲际导弹、军舰和地面机动指挥系统等)几乎都毫无例外地需要配备先进的光电对抗装备。为了有效地发挥光电对抗装备的效能,必须对来袭目标进行准确定位。由于红外单站无源(或被动)定位技术具有体积小、自身隐蔽性好和机动性高等诸多的优点,因此它在现代战争中具有重要的应用前景。
     定位包含定向和测距两个方面,其中定向技术在制导跟踪中研究甚多,且比较成熟;而测距、尤其光电单站被动测距技术是实现光电定位的关键,也是现代军事高科技中一个十分重要而又急需解决的技术难题。本文结合“十五”武器装备预研项目“机动目标红外单站被动定位技术”进行,并就空中高价值机动测量平台对机动目标的红外单站被动定位的具体问题和其中的关键技术进行了深入的研究。
     本文在分析国外国内多年来红外被动定位研究动态的基础上,深入地研究了基于交叉定位原理的被动测距和基于红外光学成像的被动测距。
     在基于交叉定位原理的被动测距研究中,导出了机动测站对静止目标测距的误差分析表达式,完善了基于测角及测时的对运动目标定位方案。重点研究和分析了一种基于短基线的准单目视觉被动定位方案,该方案对运动目标和静止目标均有效,但该方案系统所占空间较大不宜用于机载或弹载平台。
     在基于红外光学成像的被动测距研究中,针对几何光学成像,具体分析了聚焦法被动测距、离焦法被动测距、基于OTF函数或MTF函数的被动测距的原理,并统一用点扩散函数对其进行描述;对目标运动状态及投影关系,论述了相关的被动测距,如小平面运动分析、膨胀测距、外标法测距;对目标红外辐射的传输特性,进行了基于连续观测目标辐射强度的被动测距的研究。重点开展了为IRSTS(红外警戒系统)装备单波段红外被动测距功能的研究,结合角度信息和美国海军红外传输模型,得到了一个综合性的被动测距公式。该公式适用于工作于灵敏度受限模式下的系统、且要求有关参数选择正确。
     针对上述现有各种被动定位方案的不足或局限性,本项目研究并提出了基于图像序列测量的红外成像单站被动定位方案,并结合光电单站定位工程使用中的实际问题,本文研究了一种基于目标特征线度和角度测量的红外成像单站被动定位实施方案。论证了其原理,推导了相应的定位算法。针对定位方程在实际应用中的唯一性、稳定性和可解性问题,开展了对定位算法方程之解的研究,证明了定位算法的唯一性和稳定性,通过仿真分析进一步证明了定位方程的可解性。
     本文以定位算法的工程适用性为导向,开展了相关研究,包括(1)被动测距的性能分析,指出目标特征线度的测量误差是影响定位精度的主要因素,给出了在不同情况下,保精度定位对目标特征线度尺寸测量误差的要求;(2)为了使算法能够有效地适应机动目标姿态和运动状态的变化,讨论了特征线度的选取,研究并优化了目标特征线度和定位方程的关系;(3)序列图像处理算法对环境适应性的研究,实现了了云、雨等复杂环境下目标图像的平滑、增强,结合目标图像的边缘检测及特征匹配获得了目标的特征线度,最后获得了亚像素级的目标特征线度。(4)设计并组建了计算机控制的半实物缩比仿真系统,进行了大量的试验研究,其中包括目标运动状态和姿态、观测站机动状况对定位性能影响的研究,并在半实物仿真实验的基础上验证和完善了定位算法。
     计算机仿真和大量半实物缩比仿真实验表明,在现有系统的图像和角度等参数的测量精度范围内,其定位误差不大于5%斜距,满足技术指标要求,验证了本文所提定位算法的正确性和有效性。
     文章最后总结了本论文的工作,对红外单站被动定位技术的进一步研究和应用给出了个人的观点。
Along with the rapid progress of the modern military technology, the electro-optical countermeasure techniques have gained its rapid development and wide application in modern warfare, among them the advanced electro-optical countermeases equipments are needed for fitting all high-value mobility platform without exception, such as the Strategy Bomber, Early Warning Aircraft, Intercontinental Ballistic Missile, War Ship and Ground Core Command System. For giving full play to the efficiency of electro-optical countermeasure equipments, that accurate location to a intruding target is needed, it is also an important technology which urgently to be solved in modern military high science and technology. The passive location system on monostation has earned its bright application prospect in modern warfare, for its merit of small size, good self-concealing and high mobility.
     Location includes both direction and ranging, the direction technology is becoming perfect because it has been widely studied in guide and tracking, but the ranging technology, especially ranging on monostation based on electro-optical techniques is yet the key technology, it is also an important technology which urgently to be solved in modern military high science and technology. Combined with the tenth-five-year Weapon Equipment Front Research Item that the passive infrared location Technology on monostation, this dissertation deals with the particular problems and the key technology in passive infrared mono-station location to mobile targets from aerial high-value mobile platform.
     On the basis of investigating in both abroad and domestic trend of passive location research in the past years, it performs a deeper research into the passive ranging based both on principle of intersection of lines-of-sight, and on the infrared imaging bounds to a moving spatial target.
     On the research of passive ranging based on intersection of lines-of-sight, a closed error analysis formula is obtained for stillness targets ranging from a mobile observation station, the location schemes based on either angle measuring or synchronous timing was evolved or consummated. The emphasis was put on a quasi-monocular passive location strategy with a short baseline. This strategy is valid for both stillness and movement target, but the corresponding system is not suitable for an airbone platform because of its large space requirement.
     In the study of passive ranging target based on infrared optics imaging, to counter the geometrical optics bound, passive ranging that based on focusing, on defocusing, on Optical Transfer Function, and on Modulation Transfer Function were analyzed individually, all of these were described in the Point Spread Function frame. To counter spatial relationship and projective bound, the passive ranging schemes based on affin transfer were discussed, which involves the facet movement analysis, the contour expand based ranging, ranging with an external base line. To counter the infrared signal propagation characteristic, the passive ranging based on radiant intension observed successively was investigated. It focused on how to equip ranging function for an Infrared Searching and Tracking System, a global passive ranging scheme has achieved combined the United States navy model with the directional information. This scheme is feasible for a system work under sensitivity-limited, and correct parameters setting is needed.
     With the defects or limitations of each scheme available having been countered, a passive Infrared monostation ranging scheme based on image sequence measurement was turned out, and then combined with the practical problem in engineering realization, an executive scheme was studied based on the targets'characteristic linearity combined with the directional information. The location principle was proved, and the relative location algorithm equations were turned out. To counter the exclusive, steady and existent property of the location algorithm, a research on the solution to the location equations was performed; the ranging algorithm was demonstrated exclusive and steady. It also was affirmed further by simulation that the location algorithm would not lose its stability in practice using.
     Aiming at engineering realization for the this algorithm, relative research has performed, which include:(1) the performance analysis, and it was made clear that the characteristic linearity measurement error is the main factor for location precision, then the characteristic linearity measurement limitation for location within certain precession has given. (2) For letting this algorithm effectively fit the variation of the target's posture and movement state, the characteristic linearity choice was studied, and the relationship between characteristic linearity and the location equations has been discussed and optimized. (3) The study of the adaptability of image sequence procession algorithm to the target's surroundings, as the target images filtration and enhancement under such complicated surroundings such as clouds and rain, the characteristic linearity was found through the target's edge detection and trace matching, subsequently a characteristic linearity in subpixel has obtained. (4) A quasi-reality reduce scale model simulation system was designed and build up, with which lots of experiments research was carried out, those involve location performance via mobile target's posture, via target's movement state, and via measurement station's movement state, the relative location algorithm has tested and consummated.
     It is illustrated by both computer simulating and lots of experiments under the quasi-reality reduce scale model simulation system, that a relative ranging error less than 5% can be achieved within image measuring precision and goniometer measuring precision in our exiting system. The results meet specification requirement, the correctness and the validity of the algorithm has been tested and verified again.
     At last, an overview of the paper was given together with the author's personal view on the deeper research and application for infrared passive location techniques on monostation for the future.
引文
[1]于艳梅编译,用于空战的无源目标探测迅速发展[J],光电对抗与无源干扰,1999(2):40-46.
    [2]胡进,对空红外无源探测警戒系统关键技术浅述[J],雷达与对抗1999(2):9-15.
    [3]单洪春,无源探测雷达发展初探[J],航天电子对抗,2003(3):22-25.
    [4]王建刚,朱元清,毛五星,机载无源定位系统的多点定位机精度分析[J],空军雷达学院学报,2003:17(3):28-30.
    [5]孙仲康,周一宇,何黎星,单多基地有源无源定位技术[M].北京:国防工业出版社,1996年.
    [6]王昭,相明,李宏等.一种基于瞬时频率估计的被动声学测距方法[J].兵工学报,2000,21(2):129-131.
    [7]张正明.辐射源无源定位技术研究[D].西安:西安电子科技大学电子工程学院,2000.10-25
    [8]安毓英,刘劲松.激光单站定位接收机研究方案论证报告[R].西安:西安电子科技大学,1994.25-55.
    [9]Reilly J P, Youkins L T, Taylor R J. Infrared passive ranging using sea background for accurate sensor registration[J]. SPIE.1995,2469: 319-329.
    [10]Reilly J P, Klein T, Ilver H. Design and demonstration of an infrared passive ranging[J]. John hopkings APL technical digest.1999,20(2): 1854-1859.
    [11]Ronald J Pieper, Alfred W Cooper, G Pelegris. Passive range estimation using dual-baseline triangulation[J]. Optical Engineering.1996,35(3). 685-692.
    [12]赵春晖,赵枫.多站点准单站无源定位技术的研究[J].制导与引信.1996, (2):33-37.
    [13]Berle F. J. Mixed Triangulation/Trilateration Techniques for Emitter Location[C]. Proc. IEE part F.1986,133(7).
    [14]何友金,陆斌.红外告警器对目标定位方法研究[J],光电对抗与无源干扰1997,(1):13-17.
    [15]K. C. Ho, Y. T. Chan. Solution and performance analysis of geolocation by TDOA[J]. IEEE Trans. On AES.1993,10,29(4):1311-1322.
    [16]K. C. Ho. Geolocation of known altitude object from TDOA and FDOA measurements[J]. IEEE Trans. On AES.1997,33(3):770-782.
    [17]P. S. Ray. A novel TOA analysis technique for radar identification [J]. IEEE Trans. On AES.1998,34(3):716-721.
    [18]付小宁,李西安.单站被动定位及光电实现[J].测试技术学报,2002,16(1):45-47.
    [19]安毓英,曾小东,刘劲松.激光单站被动测距技术研究[J].激光技术.1998,22(2):129-130.
    [20]Baldacci A, Corsini G, Diani D. Ranging by means of monocular passive systems[J]. Proceedings of SPIE Conference on signal processing, Sensor fusion and Target recognition.1999,3720:473-482.
    [21]Jeffrey W, Draper J S, Gobel R. Monocular Passive Ranging[J]. Proceedings of IRIS Meeting of Special Group on Targets, Backgrounds and Discrimination.1994.113-130.
    [22]Mckay D L, Wohlers R, Chuang C K. Airborne validation of an IR passive TBM ranging sensor[J]. Proceedings of SPIE Conference on Infrared Technology and Applications.1999,3698:491-500.
    [23]Randall P. Kinematic ranging for IRSTs. SPIE.1993, Vol.1950:96-104.
    [24]付小宁.关于基线单站被动测距[J].激光与红外.2001,31(6):374-376.
    [25]李象霖.三维运动分析[M].中国科技大学出版社,1996.
    [26]Larry Matthies, Takeo Kanada, Kalman filter-based algorithm for estimating depth from image sequence [J]. International Journal of Computer Vision,1989, Iss 3:209-236.
    [27]钟平,冯进良,于前洋等.动态图像序列帧间运动补偿方法探讨[J].光学技术,2003,29(4):441-444.
    [28]陈衡.红外物理学[M].北京:国防工业出版社.1985.1-125.
    [29]白长城,张海兴,方湖宝.红外物理[M].北京:电子工业出版社.1989.3-69.
    [30]刘景生.红外物理[M].北京:兵器工业出版社.1992.1-89.
    [31]周书铨.红外辐射测量基础[M].上海:上海交通大学出版社.1990.1-57.
    [32]韦毅,杨万海,李红艳.红外三维定位精度分析[J].红外技术,2002,24(6):37-40.
    [33]程兵旺.机动多目标红外无源单站被动定位新技术研究[D].西安:西安电子科技大学.1998,1.
    [34]肖旸.红外无源单站定位技术[D].西安:西安电子科技大学.2000,1.
    [35]多目标红外单站被动定位技术[R].GF报告,2001年4月.
    [36]对机动平台的光电单站定位技术[R].十五武器装备预先研究开题论证报告,2002年6月.
    [37]赵勋杰,高稚允.光电被动测距技术[J].光学技术,2003,29(6):652-656.
    [38]E. R. Dowski Jr, W. T. Cathey. Single lens single-image incoherent passive ranging systems [J]. Application Optics,1994,33(29):6762-6773.
    [39]吴晗平.红外警戒系统的被动测距方法研究.电光与控制.1998,71(3):21-26.
    [40]侯娜,黄道君.红外无源定位技术研究[J].电子对抗技术.2002,17(4):12-15.
    [41]陈前荣.单站红外被动定位系统[J].激光与光电子学进展(增刊).1999,(9):27-30.
    [43]谢邦荣.机载红外被动定位方法研究[J].红外技术.2001,23(5):1-3.
    [44]路远,时家明等.红外被动定位研究[J].红外与激光工程.2001,12,30(6):405-409.
    [45]王刚,禹秉熙.基于对比度的空中红外点目标探测距离估计方法[J].光学精密工程.2002,10(3):276-280.
    [46]钱铮铁.一种用于红外警戒系统的被动测距方法[J].红外与毫米波学报.2001,20(4):311-314.
    [47]张国平,明海,谢建平等.像素高频振动用于实现被动测距[J].电子学报,26(8):123-125.
    [48]郭福成,孙仲康,安玮.利用方向角及其变化率对固定辐射源的三维单站无源定位[J].电子学报,2002,30(12):1885-1887.
    [1]西南技术物理研究所《红外技术》编辑部编译.红外和光电系统手册[M].231-240,1995年.
    [2]Mao Longbin, Xu Yaowei, Zhou Yiyu, Sun Zhongkang. Bearing-only location using nonlinear least squares[J]. IEEE Trans. on AES,1997, AES-33(4):1042-1044.
    [3]邓新蒲,周一宇.单观测器无源定位误差下界的仿真分析[J].电子与信息学报,2002,24(1):54-59.
    [4]郭福成,孙仲康,安玮.利用方向角及其变化率对固定辐射源的三维单站无源定位[J].电子学报,2002,30(12):1885-1887.
    [5]韦毅,杨万海,李红艳.红外三维定位精度分析[J].红外技术,2002,24(6):37-40.
    [6]付小宁,关于基线单站被动测距[J].激光与红外,2001,31(6):374-376.
    [7]孙仲康,周一宇,何黎星,单多基地有源无源定位技术[M].北京:国防工业出版社,1996年.
    [8]Reilly J P, Youkins L T, Tailor R J. Infrared passive ranging using sea background for accurate sensor registration[C]. Proc. SPIE 2469, 318-329(1995).
    [9]Ronald J. Pieper, Alfred W Cooper, and G. Pelegris. Passive range estimation using dual-baseline triangulation[J]. Optical Engineering, 1996,35(3):685-692;
    [10]谢邦荣.机载红外被动定位方法研究[J].2001,23(5):1-3.
    [11]陈前荣.单站红外被动定位系统[J].激光与光电子学进展(增刊),1999,9:27-30.
    [12]肖旸.红外无源单站定位技术[D].西安:西安电子科技大学技术物理学院,2000年1月.
    [13]J. Patrick Reilly, Troy Klein, and Hillar liver. Design and demonstration of an infrared passive ranging[C]. John Hopkins APL technical digest,1999,20(2):220-235.
    [14]祝世平,强锡富.基于坐标测量机的双目视觉测距误差分析[J].电子测量与仪器学报,1996,14(2):26-31.
    [15]付小宁,殷世民,刘上乾.基于系统非线性的红外焦平面非均匀性校正[J].光子学报,2002,31(10):1277-1280.
    [16]张善钟.精密仪器精度理论[M].北京:机械工业出版社,1993年.
    [1]O. Faugeras. Three-Dimensional Computer Vision:A Geometric Viewpoint [M]. MIT Press,1993.
    [2]Gerald C. Hoist. Electro-Optical Imaging System Test and Evaluation [M]. second edition, SPIE OPTICAL ENGINEERING PRESS,2000.
    [3]Gerald C. Hoist. Electro-Optical Imaging System Performance[M]. second edition, SPIE OPTICAL ENGINEERING PRESS,2000.
    [4]祝世平.大型工件特征点空间坐标视觉检测方法研究[D].哈尔滨工业大学博士论文.
    [5]G. Lighart, et al. A comparison of different autofocus algorithms[J]. IEEE Computer Society Conf. Computer Vision and Pattern Recognition,1982: 597-600.
    [6]H. Harms, et al. Comparison of digital focus criteria for a TV microscope system[J]. Cytometry,1984,5:236-243.
    [7]F. C. Groen, et al. A comparison of different focus functions for use in autofocus algorithms[J]. Cytometry,1985,6:81-91.
    [8]L.Firestone, et al. Comparison of autofocus method for automated microscopy[J]. Cytometry,1991,12:195-205.
    [9]R. A. Jarvis, Focus Optimization Criteria for Computer Imaging Procession[J]. Microscope,1976,24:163-180.
    [10]M.Subarao, et al. Depth from Focus and Autofocusing:A Practical Approach[J]. IEEE Computer Vision Society Conf. Computer Vision and Pattern Recognition,1992:773-776.
    [11]M. Subarao, et al. Focusing Techniques Optical Engineering[J].1993, 32(11):2824-2836.
    [12]M. Subarao, et al. Accurate recover of Three-dimension Shape from image Focus[J]. IEEE Trans on. Pattern Analysis and Machine Intelligence,1995, 17(3):266-274.
    [13]M. Subarao, et al. Depth Recover from Blurred Edges [J]. IEEE Computer Vision Society Conf. Computer Vision and Pattern Recognition.1988: 498-503.
    [14]M. Subarao, et al. Computer Modeling and simulation of Camera Defocus[J]. SPIE 1992,1822:110-120.
    [15]M. Subarao, et al. Aplication of Spatial-Domain Convolution /Deconvolution Transform for Determine Distence from Image Defocus[J]. SPIE 1992,1822:159-167.
    [16]G.Surya, et al. Depth from Defocus by changing camera Aperture:A Practical Approach [J]. IEEE Computer Vision Society Conf. Computer Vision and Pattern Recognition.1993:61-67.
    [17]M.Subarao, et al. Depth from Defocus:A Spatial Domain Approach[J]. International Journal of computer vision,1994,13(3):271-294.
    [18]Jarvis R A. A perspective on ranging finding techniques for computer vision [J]. IEEE Trans on Pattern Anal. Machine Intel,1983 (PAMI 5):122-139.
    [19]赵勋杰,高稚允.光电被动测距技术[J].光学技术,2003,29(6):652-656.
    [20]A. P. Pentland, et al. A simple real-time ranging camera[J]. IEEE Computer Vision Society Conf. Computer Vision and Pattern Recognition.1989: 256-261.
    [21]J. Eens. A investigation of method for determine depth from focus [J]. IEEE Trans on. Pattern Analysis and Machine Intelligence.1993,15(2): 97-108.
    [22]E. R. Dowski Jr, W. T. Cathey. Single lens single-image incoherent passive ranging systems[J]. Application Optics,1994,33(29):6762-6773.
    [23]Johnson. G. E, Dowski. E R, Caththey W T:Passive ranging through wave-front coding:information and application[J]. Application optics, 2000,139(11):1700-1710
    [24]张国平、明海,谢建平等.像素高频振动用于实现被动测距[J].电子学报,26(8):123-125.
    [25]Fu Guangjie, Huang Shenghua, Zhang Guoping, Ye Jiaxiong. Novel passive ranging method using pixel dither[J]. Proc. of SPIE,1995,2599:64-72.
    [26]M.波恩,E.沃尔夫,光学原理(中译本第二版)[M].北京:科学出版社,1985:568-678.
    [27]徐立中,数字图像的智能信息处理[M].北京:国防工业出版社,2001年7月.
    [28]马颂德 张正友,计算机视觉——计算理论与算法基础[M].北京:科学出版社,1998.1.
    [29]Baldacci A, Corsini G, Diani D. Ranging by means of monocular passive systems[J]. Proceedings of SPIE Confrence on signal processing, Sensor fusion and Target recognition,1999,3720:473-482.
    [30]梁晓云,曾卫明,章品正等.基于小波滤波器组的光流估计[J].数据采集与处理,2004,19(1):78-81.
    [31]曹闻,李弼程,邓子建.一种基于小波变换的图像配准方法[J].2004,2:16-19.
    [32]Larry Matthies, Takeo Kanada, Kalman filter-based algorithm for estimating depth from image sequence [J]. International Journal of Computer Vision 1989:Iss 3,209-236.
    [33]Dalmia A K, Trivedi M. Target ranging using passive sensing approaches[J]. SPIE,1995,2469:363-370.
    [34]Reilly J P, Younkins L T, Taylor R J. Infrared passive ranging using sea background for accurate sensor registration [J]. SPIE,1995, Vol.2469: 318-329.
    [35]孙仲康,周一宇,何黎星.单多基地有源无源定位技术[M].北京:国防工业出版社.1996.5.
    [36]何友,关欣,衣晓.纯方位二维运动目标的不可观测性问题研究[J].系统工程与电子技术,2003,25(1):11-14.
    [37]Jeffrey W, Draper J S, Gobel R. Monocular Passive Ranging[J]. Proceedings of I RI S Meeting of specialty Group on Targets, Backgrounds and. Discrimination.1994,113-130.
    [38]Mckay D L, Wohlers R, Chuang C K. Airborne validation of an IR passive TBM ranging sensor[J]. Proceedings of SPIE Conference on Infrared Technology and Applications 1999,1699:491-500.
    [39]吴晗平.红外警戒系统的被动测距方法研究[J].电光与控制,1998,(3):21-26.
    [40]Hudson R D. Infrared System Engineering[M]. Wiley and Sons, INC.1969.(红外系统原理翻译组译,红外系统原理,北京:国防工业出版社),1975.
    [41]姜宏滨.舰载红外警戒系统中的距离估算[J].红外与毫米波学报,1999,18(6):438-442.
    [42]钱铮铁.一种用于红外警戒系统的被动测距方法[J].红外与毫米波学报,2001,20(4):311-314
    [43]肖肠.红外被动定位技术研究[D].西安电子科技大学硕士学位论文,2000,3.
    [1]孙仲康,周一宇,何黎星.单多基地有源无源定位技术[M].北京:国防工业出版社,1996年
    [2]谢邦荣.机载红外被动定位方法研究[J].红外技术,2001,23(5):1-3
    [3]钱铮铁.-种用于红外警戒系统的被动测距方法[J].红外与毫米波学报, 2001,20(4):311-314
    [4]付小宁.关于基线单站被动测距[J].激光与红外,2001,31(6):374-376.
    [5]姜光.基于二次曲线的单轴旋转运动分析和三维重建[D].西安电子科技大学博士论文,2004年12月.
    [6]苏大图.光学测量[M].机械工业出版社,1987.
    [7]高文,陈熙霖.计算机视觉——算法与系统原理[M].清华大学出版社/广西科学技术出版社,1999年,第1版
    [8]付小宁,刘上乾,申建华.借助特征线度的飞机被动定位研究[J].电子测量与仪器学报(已录).
    [9]杨孝先,尹业富.确定空间曲线参数方程的一般方法[J].数学通报,1996,(3)27-28
    [10]欧阳芳锐,张玉平译/图马著.工程数学手册(第4版)[M].北京:人民教育出版社,2002年1月.
    [11]荣现志,张顺忠译,W.H.拜尔编.标准数学手册(第26版)[M].北京:化学工业出版社1988年12月.
    [12]张光岚.三维空间下机动目标自适应滤波器设计与仿真[D].西北工业大学八系,1998年2月.
    [13]吴立德.计算机视觉[M].上海:复旦大学出版社,1993.
    [14]梁晓云,曾卫明,章品正等.基于小波滤波器组的光流估计[J].数据采集与处理,2004,19(1):78-81.
    [15]钟平,冯进良,于前洋等.动态图像序列帧间运动补偿方法探讨[J].光学技术,2003,29(4):441-444.
    [16]肖旸.红外无源单站定位技术[D].西安:西安电子科技大学,2000
    [17]殷世民,付小宁,刘上乾.红外单站被动定位技术速度更新算法研究[J].光子学报,2003,32(3):298-300
    [1]胡浩,王明照,杨杰.自适应模糊加权均值滤波器[J].系统工程与电子技术,2002,24(2):15-17.
    [2]田捷,沙飞,张新生.实用图像分析与处理技术[M].电子工业出版社,1995.
    [3]李宏贵.非线性滤波器在红外图像增强中的应用[J].数据采集与处理,1999,14(3):302-305.
    [4]蔡靖,杨晋生,丁润涛.模糊加权均值滤波器[J].中国图象图形学报,2000,5(A/1):52-56.
    [5]王保平,范九伦,谢维信.基于直方图和区域信息的图像去噪滤波器[J].西安电子科技大学学报.30(3):340-344.
    [6]Wang J H, Lin L D. An Improved Median Filter Using Minmax Algorithm for Image processing[J]. Electron Lett,1997,33(16):1362-1363.
    [7]Brownrigg D R K. The Weighted Median Filter[J]. Comm Ass Comput Mach, 1984,27(8):807-818.
    [8]Arce G R, Foster R E. Detail Preserving Ranked order Based Filters for Image Processing[J]. IEEE Trans on ASSP,1989,37(1):83-89.
    [9]Sun T, Neuvo Y. Detail-preserving Median Based Filters in Image Processing[J]. Pattern Recognition Lett,1994,15(4):341-347.
    [10]Yu P, Lee C S. Adaptive Fuzzy Median Filter[A]. Proc Int Symp Artificial Neural Networks[C]. London:Elsevier Science Publishers B V,1993.318-362.
    [11]Wang J H, Yu M D. Image Smoothing by Adaptive Fuzzy Optimal Filter[A]. Proc IEEE Int Conf Syst Man, and Cybern[C]. New York:IEEE Computer Society Press,1995.845-848.
    [12]高新波,谢维信.基于小波变换的分形噪声白化滤波器[J].西安电子科技大学学报,1998,25(5):565-569.
    [13]张丽,陈志强,高文焕等.均值加速的快速中值滤波算法[J].2004,44(9):1157-1159.
    [14]Makoto Nagao, Takashi Malsuyams. Edge Preserving Smoothing[J]. Computer Graphics and Image Processing.1979,9:394-407.
    [15]Richard N. Czerwinski, Douglas L. Jones, William D.0'Brien. Ultrasound Speckle Reduction By directional Median Filtering[C]. Image Processing Proceeding International Conference,1995,1:358-361.
    [16]G. R.Arce, Multistage order statistic filters for image sequence processing [J]. IEEE Trans. on Signal Processing,1991,39(5),1146-1163.
    [17]余庆军,谢胜利,一个基于相邻像素兼容度的模糊加权平均滤波器[J].通信学报,24(12):1-8.
    [18]刘丽梅.可保留细节信息的全方位多级组合滤波法的研究[J].计算机应用与软件,21(5):127-128.
    [19]Lee C S, Kuo Y H, Yu P T. Weighted Fuzzy Median Filters for Image Processing[J]. Fuzzy Sets System,1997,89(2):157-180.
    [20]朱菊华,杨新,李俊.一种改进的自适应保细节中值滤波算法[J].计算机工程与应用,2001,3:93-95.
    [21]Kenneth. R. Castleman著,朱志刚等译.数字图像处理(Digital Image Processing) [M].电子工业出版社/PRENTICE HALL出版公司,1998年9月.
    [22]熊兴华,钱曾波,陈鹰等.基于遗传优化的分段线性影像增强[J],测绘学报.2004,33(4):341-346
    [23]Pizer S. Adaptive histogram equalization and its variations[J]. CVGIP,1987,39(3):355-368.
    [24]Silverman J, Mooney J M. Vickers V E. Display of wide dynamic range infrared images from PtSi chottky barrier cameras [J]. Optical Engineering, 1990,29(2):97-104.
    [25]Pizer S. Adaptive histogram equalization and its variations[J]. CVGIP,1987,39(3):355-368.
    [26]J. G. M. Schavemaker. Image Sharpening by Morphological Filtering [J]. Pattern Recognition,2000,33:997-1012.
    [27]Van den Boomgaard R, Smeulders A. The morphological structure of images, the differential equations of morphological scale-space[J]. IEEE Transactions PAMI,1994,16(11):1101-1113.
    [28]王耀革,王玉海,朱长青等.基于灰度形态学的高分辨率遥感影像预处理[J],测绘学院学报.2004,21(2):108-110
    [29]孙伟,夏良正.基于形态学梯度的红外图像分割算法[J],信号处理.2004,20(1):10-14
    [30]章毓晋.图象工程(上册)——图象处理与分析[M].北京:清华大学出版社,1999年.
    [31]PAL S K. Image Enhancement Using Smoothing with Fuzzy Sets. IEEE, 1981, SMC.11(7):494-501.
    [32]S. K. Pal and R.A.King. On edge detection of X-ray images using fuzzy sets[J]. IEEE Trans. Pattern Analysis and Machine Intelligence,1983, 5(1):69-77.
    [33]裴继红,谢维信.基于平滑性测度的直方图自适应模糊增强图像分割[J].信号处理,1999,15(Z):1-6.
    [34]杜亚娟,潘泉,周德龙等.图像多级灰度非线性模糊增强算法研究[J].数据采集与处理.1999.14(2):140-143.
    [35]张飞,李承芳.红外背景抑制与弱小目标的检测算法[J],光学技术.2004,30(3):337-342
    [36]张新明,沈兰荪.基于小波和统计特性的自适应图像增强[J],信号处理.2001,17(3):227-231
    [37]S. Mallat, et al. Characterization of signals from multiscale Edge[J]. IEEE Transactions PAMI,1992,14(7):710-732.
    [38]J C Olivo. Automatic threshold selection using the wavelet transform[J]. CVGIP:Graphical Models and Image Procession.1994,56(3): 205-218.
    [39]贾天序,郑南宁,黄小虎等.基于一类中心B样条二进小波的多尺度边缘提取[J].西安交通大学学报.1996.30(1):91-95.
    [40]解梅,顾德仁.使用小波变换的图像边缘检测算法[J].电子科技大学学报.1996.25(4):353-356.
    [41]邓念斌,陈作炳.基于分形特征的医用图像边缘增强和检测[J].湖北汽车工业学院学报2002,16(1):36-39.
    [42]戴青云,余英林.一种基于形态小波的在线掌纹的线特征提取方法[J].计算机学报.2003,26(2):234-238.
    [43]Nalwa VS, Binford T O. On deteccting edges [J]. IEEE Trans on PAMI, 1986,8(6):699-714.
    [44]Haralick R M. Digital step edges from zero crossing of second directional derivatives[J]. IEEE Trans on PAMI,1984,6(1):58-68.
    [45]罗西平,田捷,诸葛婴等.图像分割方法综述[J].模式识别与人工智能,1999,12(3):300-312.
    [46]J. Canny. Acomputational approach to edge detection[J]. IEEE Trans on PAMI,1986,8(6):679-698.
    [47]W. H. H. J. Lunscher, et al. Optimal edge detector design:Parameter selection and noise affections[J]. IEEE Trans on PAMI,1986,8(2): 164-177.
    [48]W. H. H. J. Lunscher, et al. Optimal edge detector design Ⅱ Coefficient quantization[J]. IEEE Trans on PAMI,1986,8(2):178-187.
    [49]V. S. Nalwa, et al. On detecting edges[J]. IEEE Trans on PAMI,1986, 8(6):699-714.
    [50]王艳丽,陈哲.基于模糊和最小二乘的SAR图像线特征提取[J].北京航空航天大学学报,2003,29(4):342-345.
    [51]王广君,田金文,柳健.基于四叉树结构的图像分割技术[J].红外与激光工程,2001,30(1):12-14.
    [52]张灵,章云,杨宜民.基于模糊聚类的缺损图像的边缘检测[J].计算机工程,2004,30(2):21-22.
    [53]Hojjatoleslami S A, Kittler J. Region Growing:A New Approach[J] IEEE Transactions on Image Processing,1998,20(8):1079-1084.
    [54]Hansen W M, Higgin W E. Relaxation method scheme and its application to edge detection[J]. IEEE PAMI,1997,19(9):946-962.
    [55]German S, German D. Stochastic relaxations, Gibbs distribution and Bayesian restoration of images[J]. IEEE PAMI,1984,6(6):799-813.
    [56]冯国进,顾国华,陈钱.基于形态学的红外图像边缘增强[J].激光与红外2003,33(6):453-454.
    [57]戴青云.数学形态学在图像处理中的应用进展[J].控制理论与应用,2001,18(4):478-482.
    [58]J. A V Meighem, et al. Straight line extraction using iteration total least square methods[J]. Journal of Visual Communication and Image Representation.1995,6(1):59-68.
    [59]M. J J Wang, et al. A new edge detection method through template matching [J]. International Journal of Patern Recognition and Artificial Intelligence.1994,8(4):899-917.
    [60]M. Gokmen, et al. Edge detection and surface reconstruction using refined regularization [J]. IEEE PAMI,1993,15(5):492-499.
    [61]李映,焦李成.基于自适应免疫遗传算法的边缘检测[J].中国图象图形学报,2003,8(8):890-895.
    [62]A D Kulkarni, G B Giridhar, Parveen Coca. Neural Network Based Fuzzv Logic Decision System for Multispectral Image Analysis [J]. Neural, Parallel & Scientific Computation,1995:(3),205-218.
    [63]Ghosals Mehrotra, R. Orathogonal. Moment operators for subpixel edge detection[J]. Pattern Recognition.1993,26(2):295-306.
    [64]D J Park, et al. Edge-detection in noisy image based on the co-occurrence matrix[J]. Pattern recognition.1994,27(6):767-775.
    [65]S N Srihari, et al. Analysis of textual image using the Hough transform[J]. Machine Vision and Applications,1989,2(3):141-153.
    [66]W E Higgins, et al. Edge detection using two-dimension local structure information [J]. Pattern recognition.1994,27(6):767-775. 1994,27(2):277-294.
    [67]马苗,樊养余,谢松云等.基于灰色系统理论的图象边缘检测新算法[J].中国图象图形学报,2003,8(10/A):1136-1139.
    [68]M M Fleck. Some defects in finite-difference edge finders [J]. IEEE Trans on PAMI,1992,14(3):337-345.
    [69]A Huteras, et al. Detection of intensity changes with suppixel accuracy using Laplace-Gaussial masks [J]. IEEE Trans on PAMI,1986, 8(5):651-664.
    [70]Gerald C. Holst, Electro-Optical Imaging System Performance[M]. second edition, SPIE OPTICAL ENGINEERING PRESS,2000.
    [71]邹仲中.提高CCD尺寸分辨力的解调测量法[J].仪器仪表学报,1986,7(1):38-44.
    [72]E P Lyvers, et al. Suppixel measurement using a moment-based edge operator[J]. IEEE Trans on PAMI,1989,11(12):1293-1309.
    [73]丁兴号,邓善熙,杨永跃等.基于空间矩和Zernike矩的亚像素边缘检测[J].2004,22(2):191-194.
    [74]黄莎白.基于样条函数的灰度图像插值[J].信息与控制,1989,(2):48-51.
    [75]A Hachicha, et al. Subpixel edge detection for precise measurements by a vision system [J]. ISPIE,1988,1010:148-157.
    [76]武拴虎,谈正.盈亏修正法图象边缘检测[J].中国图象图形学报,2000,5(6/A):493-496
    [77]S. S Gleqson, et al. Subpixel measurement of image features based on paraboliod surface [J]. ISPIE,1990,1386:135-1144
    [78]吴晓波等.应用多项式插值提高CCD尺寸测量的分辨力[J].仪器仪表学报,1996,17(2):154-159.
    [79]杨敏,叶邦彦,牟丽等,机械零件图像中直线边缘亚像素定位方法[J].华南理工大学学报,31(12):30-33.
    [80]陈卫兵,束慧.快速边缘匹配算法研究[J].计算机工程与设计,2004,25(1):130-132.

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700