靶场动平台光学测量问题研究
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摘要
导弹、炮弹等武器飞行的外弹道及姿态等参数是武器试验鉴定及故障分析的基本依据。武器试验靶场一般利用布置在若干固定点位上的多台光电经纬仪或高速摄影(像)机等光学测量设备，分别对目标进行跟踪拍摄，多站交会测量目标的外弹道与姿态等参数。但这种固定式测量方式作用范围有限，不能灵活机动布站，为了满足具有大航程、长航时、机动性强等特点的现代武器的观测需求，靶场光学测量方式正逐步从固定式向机动式发展，如车载经纬仪采用机动布站、定点测量方式，机载光测设备直接采用机动测量方式。
然而，在这些车载、机载平台上利用光学设备对运动目标实施观测还存在一些困难，其中主要有：车载经纬仪根据测量任务设置站点，其地基无法保证像固定站点般稳固，使得车载平台较易产生晃动，导致车载经纬仪难以获得高精度的测量结果；受飞机自身结构、尺寸等限制，在单架飞机上通常不能形成有效的多站交会条件，使用多机联合测量的成本又过高，现有条件下只能利用机载光测设备对运动目标跟踪拍摄，记录其飞行过程，无法测量目标的外弹道与姿态。这两个困难引申出了摄影(像)测量技术的两类基本理论问题：一类是在晃动平台(不稳定平台)上观测运动目标的问题，另一类是在机动平台上利用单站光测设备获取运动目标的轨迹与姿态的问题。本文统称这些在晃动和机动平台上利用光测设备对目标实施观测的问题为动平台光学测量问题。
针对在上述动平台上实施光学测量的问题，本文分别提出了不稳定测量平台的静态基准转换方法解决平台晃动引起的车载经纬仪测量误差的问题，以及
单目运动轨迹交会方法解决机动平台上单站光测设备对目标定位与定姿的问题，为解决目前国内靶场动平台上光测设备只能观察记录，不能高精度测量等问题提供了新的技术手段，也可适用于其它领域的类似测量问题，如不稳定测量平台的静态基准转换方法可应用于船体变形测量、机动雷达水平误差修正等领域，单目运动轨迹交会方法可应用于坦克对移动目标的定位等领域。论文的主要工作及创新点如下：
1.针对不稳定平台上的观测设备无法对运动目标实施高精度测量的问题，提出了一种基于传递像机的不稳定测量平台的静态基准转换方法。该方法通过构造一个静态基准，采用摄像测量方法，建立不稳定测量平台与静态基准的关系，消除平台不稳定引起的观测设备测量误差，即相当于将不稳定测量平台转换到一个静态基准上。该方法的基本要素包括：测量不稳定平台的晃动量，如可将固定在地面上的合作标志物作为静态基准，利用安装在不稳定平台上的传递像机拍摄这个静态基准来获得该晃动量，也可以将传递像机置于地面上作为静态基准，拍摄固定在不稳定平台上的标志物来获得这个晃动量；标定传递像机与平台，或标志物与平台间的固联关系。
2.将不稳定测量平台的静态基准转换方法应用于靶场的车载经纬仪等设备，设计了一种车载经纬仪动态误差测量与修正系统，解决了合作特征受遮挡、出视场等受干扰情况时的位姿估计、车载经纬仪的车载平台与像机固定关系标定、经纬仪测角数据误差修正等实际工程问题，在车载经纬仪上完成了一系列验证实验和实测任务实验，得到了实测过程中两种不同型号的车载经纬仪平台姿态变化量，据此修正了多次任务中车载经纬仪的测角数据，提高了利用多站测角数据交会获得的三维外弹道数据的精度。
3.利用现有的位姿估计方法测量车载经纬仪晃动时，对合作标志上特征的空间几何关系测量精度以及像机参数标定精度都有较高的要求，在车载经纬仪动态误差测量与修正系统的实施过程中不易满足。为此，提出了一种简化配置条件下车载平台姿态变化的测量方法。该方法通过两组垂直布置的测量单元(每个测量单元由一台像机和两个合作特征点组成)分别对平台两个方向上的高低和方位变化进行测量，进而得到平台的三维姿态变化量。
4.针对在飞机等机动平台上光测设备对目标单站定位的问题，提出和完善了一种运动单像机对运动目标定位的方法，即单目运动轨迹交会法。该方法突破了传统摄像测量的点交会模式，用参数化方程描述某一时间段内目标的运动轨迹，通过直接求解线性方程组得到目标运动轨迹方程参数，进而得到目标的三维位置、速度、加速度等运动参数。推导了该方法有解的充分必要条件，给出了目标轨迹方程最优阶次的确定方法，以及该方程能够最优描述的目标轨迹的时间段长度的确定方法。
5.针对在飞机等机动平台上光测设备对目标单站定姿的问题，在单目运动轨迹交会法的基础上，提出了一种单目运动像机对运动目标的定姿方法。该方法通过对目标上的若干特征点进行跟踪测量，先获取其三维运动轨迹，再根据这些特征点的相互关系，解算目标的三维姿态变化，并以这些特征点的间距不变等约束条件为准则优化目标姿态结果。
The ballistic trajectory and pose parameters of the flight object such as missile,shells, which are the basic evidences for the assessment of weapon test and failureanalysis, are measured with intersection method by multiple Optical measurementequipments such as photoelectric theodolite and high-speed photography camera(vidicon) which are placed at fixed point and are used to track and shoot the object. ButThere are some shortcomings of this kind of fixed measurement method, includingfixed effective range, no flexibility, etc. In order to satisfy the measurement demand ofmodern weapons with long-distance and long-time flight, strong maneuverability,optical measurement mode in shooting range gradually develop from the fixed one tothe mobile one, such as vehicle theodolite which works with the mode of mobilesetting,pointing measuremet, airborne optical measurement which can measure in flight.
However, there are some difficulties in moving object observation by the opticalequipments fixed on vehicle and airborne platform, mainly including: Thegroundwork of vehicle theodolite, which have to satisfy measurement demand, can’tassure as steady as the one of fixed theodolite, hence, the vehicle platform is easy toproduce a wobble which makes the theodolite difficult to obtain high accuracymeasuring results. Usually, with the limit of the structure and size, a single planecan't form valid intersection measurement conditions, it cost too much to prepare moreaircraft which calculate the results with intersection method. Currently, a singlemeasurement equipment in an airborne platform can only shoot the object and recordthe image in flight, but can not obtain the trajectory and pose parameters. Two kinds ofbasic theory problem of photogrammetry(videometrics) can be summarized from thetwo difficulties: one is moving object observation problem on disturbedplatform(unstable platform), the other one is moving object observation problem bymonocular camera on mobile platform. The optical measurement problems on unstableplatform and mobile platform are also named as “optical measurement problems onmoving platforms”, together.
In order to conquer the optical measurement difficulties on moving platforms,“conversion method for unstable platform to static reference” is proposed to eliminatethe unstable platform caused measurement error in vehicle theodolite application, and"monocular trajectory intersection method" is proposed to implement the trajectory andpose measurement of moving objects by monocular camera on mobile platform. Themethods not only provide new techniques for optical measurement equipments, whichcan only look and record the moving procedure of the object, but can not to get highprecision measuring results, in the current domestic range, but also can be applied toother fields of similar measurement problems, for example,“conversion method for unstable platform to static reference” can be applied to ship deformation measurement,correction of mobile radar level deformation measurement error and other fields,"monocular trajectory intersection method" can be applied to moving targets positioningon tank, etc. The mainly work and innovation points of the dissertation are as follows:
1.“conversion method based on relay cameras for unstable platform to staticreference” is put forward to achieve high accuracy measurement of the movement targeton unstable platform. In this method, a static reference is constructed, the relationshipbetween the reference and unstable measurement platform is measured by videometrics,then the error which is caused by unstable factor of the platform can be eliminated, i.e.,the unstable measurement platform is converted to a static reference. The basicelements include: the measurement of the wobble of the unstable platform, forexample, the wobble can be obtained by shooting a cooperation structure fixed on theground as a static reference with cameras put on the unstable platform, as well as byshooting a cooperation structure put on the unstable platform with cameras fixed on theground; the calibration for the relationship between the relay cameras and platform,or between cooperation structure and platform.
2. A measurement and correctness system based on “conversion method based onrelay cameras for unstable platform to static reference” for dynamic errors of vehicletheodolite is achieved. A lot of engineering problems such as pose estimation under thecircumstance of cooperation markers which are coverd or kept out, the calibration forthe invariable relationship between the relay cameras and platform, correctness of anglemeasuring data of theodolite,etc. A series of validation experiments and experiments insome practical tasks, which obtain the platform pose variation of two differenttheodolite, and amend angle measurement data, are accomplished and improve theprecision of3D ballistic trajectory.
3. Some requirements are not easy to be satisfied when use existing poseestimation methods to measure the theodolite wobble, such as the precision of the spacegeometric relationships between markers in cooperation structure, the precision ofcalibration for cameras, etc. Therefore, a pose variety measuring method for vehicletheodolite platform under simplified configuration conditions is proposed. Thevariations of pitch and yaw angle in two directions, which compose the3D posevariation of the platform, are detected through the two measurement units (eachmeasuring unit is composed by a camera and two cooperate feature points), respectively.
4. A positioning method for the moving object by a moving monocular camera, i.e.,"monocular trajectory intersection method", is proposed and improved for opticalmeasurement equipments in airborne platform. The method breaks through thetraditional "point meet" mode, describe one object trajectory in a period of time withparametric function, and get these parameters by solving a set of linear equations directly, then calculate the position, speed, acceleration of the object. The necessary andsufficient conditions are given, and the methods which can confirm the optimal order ofthe parametric function and the best length of time which make the function be the bestto describe the object trajectory in this period of time.
5. A pose estimation method for the moving object with a moving monocularcamera by extending "monocular trajectory intersection method" is proposed for opticalmeasurement equipments in airborne platform. The method get the trajectory of severalfeatures in an object by "monocular trajectory intersection method", and get the posevariation of the object according to the mutual relationship of these features, and theinvariability of these features such as the distance is as a criteria for pose optimization.
然而，在这些车载、机载平台上利用光学设备对运动目标实施观测还存在一些困难，其中主要有：车载经纬仪根据测量任务设置站点，其地基无法保证像固定站点般稳固，使得车载平台较易产生晃动，导致车载经纬仪难以获得高精度的测量结果；受飞机自身结构、尺寸等限制，在单架飞机上通常不能形成有效的多站交会条件，使用多机联合测量的成本又过高，现有条件下只能利用机载光测设备对运动目标跟踪拍摄，记录其飞行过程，无法测量目标的外弹道与姿态。这两个困难引申出了摄影(像)测量技术的两类基本理论问题：一类是在晃动平台(不稳定平台)上观测运动目标的问题，另一类是在机动平台上利用单站光测设备获取运动目标的轨迹与姿态的问题。本文统称这些在晃动和机动平台上利用光测设备对目标实施观测的问题为动平台光学测量问题。
针对在上述动平台上实施光学测量的问题，本文分别提出了不稳定测量平台的静态基准转换方法解决平台晃动引起的车载经纬仪测量误差的问题，以及
单目运动轨迹交会方法解决机动平台上单站光测设备对目标定位与定姿的问题，为解决目前国内靶场动平台上光测设备只能观察记录，不能高精度测量等问题提供了新的技术手段，也可适用于其它领域的类似测量问题，如不稳定测量平台的静态基准转换方法可应用于船体变形测量、机动雷达水平误差修正等领域，单目运动轨迹交会方法可应用于坦克对移动目标的定位等领域。论文的主要工作及创新点如下：
1.针对不稳定平台上的观测设备无法对运动目标实施高精度测量的问题，提出了一种基于传递像机的不稳定测量平台的静态基准转换方法。该方法通过构造一个静态基准，采用摄像测量方法，建立不稳定测量平台与静态基准的关系，消除平台不稳定引起的观测设备测量误差，即相当于将不稳定测量平台转换到一个静态基准上。该方法的基本要素包括：测量不稳定平台的晃动量，如可将固定在地面上的合作标志物作为静态基准，利用安装在不稳定平台上的传递像机拍摄这个静态基准来获得该晃动量，也可以将传递像机置于地面上作为静态基准，拍摄固定在不稳定平台上的标志物来获得这个晃动量；标定传递像机与平台，或标志物与平台间的固联关系。
2.将不稳定测量平台的静态基准转换方法应用于靶场的车载经纬仪等设备，设计了一种车载经纬仪动态误差测量与修正系统，解决了合作特征受遮挡、出视场等受干扰情况时的位姿估计、车载经纬仪的车载平台与像机固定关系标定、经纬仪测角数据误差修正等实际工程问题，在车载经纬仪上完成了一系列验证实验和实测任务实验，得到了实测过程中两种不同型号的车载经纬仪平台姿态变化量，据此修正了多次任务中车载经纬仪的测角数据，提高了利用多站测角数据交会获得的三维外弹道数据的精度。
3.利用现有的位姿估计方法测量车载经纬仪晃动时，对合作标志上特征的空间几何关系测量精度以及像机参数标定精度都有较高的要求，在车载经纬仪动态误差测量与修正系统的实施过程中不易满足。为此，提出了一种简化配置条件下车载平台姿态变化的测量方法。该方法通过两组垂直布置的测量单元(每个测量单元由一台像机和两个合作特征点组成)分别对平台两个方向上的高低和方位变化进行测量，进而得到平台的三维姿态变化量。
4.针对在飞机等机动平台上光测设备对目标单站定位的问题，提出和完善了一种运动单像机对运动目标定位的方法，即单目运动轨迹交会法。该方法突破了传统摄像测量的点交会模式，用参数化方程描述某一时间段内目标的运动轨迹，通过直接求解线性方程组得到目标运动轨迹方程参数，进而得到目标的三维位置、速度、加速度等运动参数。推导了该方法有解的充分必要条件，给出了目标轨迹方程最优阶次的确定方法，以及该方程能够最优描述的目标轨迹的时间段长度的确定方法。
5.针对在飞机等机动平台上光测设备对目标单站定姿的问题，在单目运动轨迹交会法的基础上，提出了一种单目运动像机对运动目标的定姿方法。该方法通过对目标上的若干特征点进行跟踪测量，先获取其三维运动轨迹，再根据这些特征点的相互关系，解算目标的三维姿态变化，并以这些特征点的间距不变等约束条件为准则优化目标姿态结果。
The ballistic trajectory and pose parameters of the flight object such as missile,shells, which are the basic evidences for the assessment of weapon test and failureanalysis, are measured with intersection method by multiple Optical measurementequipments such as photoelectric theodolite and high-speed photography camera(vidicon) which are placed at fixed point and are used to track and shoot the object. ButThere are some shortcomings of this kind of fixed measurement method, includingfixed effective range, no flexibility, etc. In order to satisfy the measurement demand ofmodern weapons with long-distance and long-time flight, strong maneuverability,optical measurement mode in shooting range gradually develop from the fixed one tothe mobile one, such as vehicle theodolite which works with the mode of mobilesetting,pointing measuremet, airborne optical measurement which can measure in flight.
However, there are some difficulties in moving object observation by the opticalequipments fixed on vehicle and airborne platform, mainly including: Thegroundwork of vehicle theodolite, which have to satisfy measurement demand, can’tassure as steady as the one of fixed theodolite, hence, the vehicle platform is easy toproduce a wobble which makes the theodolite difficult to obtain high accuracymeasuring results. Usually, with the limit of the structure and size, a single planecan't form valid intersection measurement conditions, it cost too much to prepare moreaircraft which calculate the results with intersection method. Currently, a singlemeasurement equipment in an airborne platform can only shoot the object and recordthe image in flight, but can not obtain the trajectory and pose parameters. Two kinds ofbasic theory problem of photogrammetry(videometrics) can be summarized from thetwo difficulties: one is moving object observation problem on disturbedplatform(unstable platform), the other one is moving object observation problem bymonocular camera on mobile platform. The optical measurement problems on unstableplatform and mobile platform are also named as “optical measurement problems onmoving platforms”, together.
In order to conquer the optical measurement difficulties on moving platforms,“conversion method for unstable platform to static reference” is proposed to eliminatethe unstable platform caused measurement error in vehicle theodolite application, and"monocular trajectory intersection method" is proposed to implement the trajectory andpose measurement of moving objects by monocular camera on mobile platform. Themethods not only provide new techniques for optical measurement equipments, whichcan only look and record the moving procedure of the object, but can not to get highprecision measuring results, in the current domestic range, but also can be applied toother fields of similar measurement problems, for example,“conversion method for unstable platform to static reference” can be applied to ship deformation measurement,correction of mobile radar level deformation measurement error and other fields,"monocular trajectory intersection method" can be applied to moving targets positioningon tank, etc. The mainly work and innovation points of the dissertation are as follows:
1.“conversion method based on relay cameras for unstable platform to staticreference” is put forward to achieve high accuracy measurement of the movement targeton unstable platform. In this method, a static reference is constructed, the relationshipbetween the reference and unstable measurement platform is measured by videometrics,then the error which is caused by unstable factor of the platform can be eliminated, i.e.,the unstable measurement platform is converted to a static reference. The basicelements include: the measurement of the wobble of the unstable platform, forexample, the wobble can be obtained by shooting a cooperation structure fixed on theground as a static reference with cameras put on the unstable platform, as well as byshooting a cooperation structure put on the unstable platform with cameras fixed on theground; the calibration for the relationship between the relay cameras and platform,or between cooperation structure and platform.
2. A measurement and correctness system based on “conversion method based onrelay cameras for unstable platform to static reference” for dynamic errors of vehicletheodolite is achieved. A lot of engineering problems such as pose estimation under thecircumstance of cooperation markers which are coverd or kept out, the calibration forthe invariable relationship between the relay cameras and platform, correctness of anglemeasuring data of theodolite,etc. A series of validation experiments and experiments insome practical tasks, which obtain the platform pose variation of two differenttheodolite, and amend angle measurement data, are accomplished and improve theprecision of3D ballistic trajectory.
3. Some requirements are not easy to be satisfied when use existing poseestimation methods to measure the theodolite wobble, such as the precision of the spacegeometric relationships between markers in cooperation structure, the precision ofcalibration for cameras, etc. Therefore, a pose variety measuring method for vehicletheodolite platform under simplified configuration conditions is proposed. Thevariations of pitch and yaw angle in two directions, which compose the3D posevariation of the platform, are detected through the two measurement units (eachmeasuring unit is composed by a camera and two cooperate feature points), respectively.
4. A positioning method for the moving object by a moving monocular camera, i.e.,"monocular trajectory intersection method", is proposed and improved for opticalmeasurement equipments in airborne platform. The method breaks through thetraditional "point meet" mode, describe one object trajectory in a period of time withparametric function, and get these parameters by solving a set of linear equations directly, then calculate the position, speed, acceleration of the object. The necessary andsufficient conditions are given, and the methods which can confirm the optimal order ofthe parametric function and the best length of time which make the function be the bestto describe the object trajectory in this period of time.
5. A pose estimation method for the moving object with a moving monocularcamera by extending "monocular trajectory intersection method" is proposed for opticalmeasurement equipments in airborne platform. The method get the trajectory of severalfeatures in an object by "monocular trajectory intersection method", and get the posevariation of the object according to the mutual relationship of these features, and theinvariability of these features such as the distance is as a criteria for pose optimization.
引文
[1]张小虎.靶场图像运动目标检测与跟踪定位技术研究[D].国防科学技术大学博士学位论文2006.
[2]何照才,胡保安.光学测量系统[M].北京:国防工业出版社,2002.
[3]刘利生.外弹道测量数据处理[M].北京:国防工业出版社,2002.
[4]张远新,齐国铭等.靶场机载电视经纬仪的发展和应用[J].测控技术,2002,22(4).
[5]何照才.国外靶场电影经纬仪现状[A]. In中国兵工学会第六届测试技术学会年会论文集[C],1992.
[6]张谦.星光-惯性复合制导系统[J].导弹与航天运载技术,1993,203(3):37-41.
[7]程国采.战术导弹导引方法[M].北京:国防工业出版社,2000.
[8]郭喜庆.基于机电一体化技术的新型寻北系统的研究和应用[R].中国科学院长春光学精密机械与物理研究所:2002.
[9]Yefimev MV. Ballistic Missile Aiming Systems[J]. Missile and Rockets,1970,123(4).
[10]A. L. Allan. The Principle of Theodolite Intersection Systems[J]. Survey,1988,29(277).
[11] Ailbert V. Jelalion. Laser Radar System[J]. Artech House,1992.
[12]张东梅.车载平台变形测量技术的研究[D].中国科学院研究生院博士学位论文2006.
[13]第三十一试验训练基地《训练教材》编写组.弹道测试[M].北京:国防科工委司令部教育训练部,1989.
[14]邹丕盛.现代科学技术与军事[M].北京:国防工业出版社,1998.
[15]文仲辉.战术导弹系统分析[M].北京:国防工业出版社,2000.
[16]史长捷.测控飞机站——测控技术的重要发展[J].遥测遥控,1991,12(3):1-8.
[17]苏成翔,房鸿瑞等.基于进化算法的测控飞机跟踪路径规划[J].飞行器测控学报,2009,28(1):82-84.
[18]中国科学院长春光学精密机械与物理研究所.机(舰)载电视经纬仪方案设计报告[R].中国科学院长春光学精密机械与物理研究所,2001.
[19]91550部队. XX导弹火控系统精度试验测量方案[R].2002.
[20]于起峰,尚洋.摄像测量原理与应用研究[M].北京:科学出版社,2009.
[21]牛忠文,程海平.雷达天线基准水平误差的一种测量方法[J].电子机械工程,2005,21(6):38-42.
[22]姜广文.像机链位姿传递摄像测量方法及船体变形测量研究[D].国防科技大学博士学位论文2010.
[23]万德钧,刘玉锋.消除舰船变形的影响和为全舰提供高精度姿态基准[J].中国惯性技术学报,2005,13(4):77-82.
[24]柳爱利,卢伟.甲板变形测量技术研究[J].海军航空工程学院学报,2009,24(2):178-180.
[25]张鹏.舰载摄像稳定平台的结构设计[J].舰船电子对抗,2006,2970-73.
[26]Xie. D L. Stabilization of line-of-sight for airborne O-E tracking and imagingsystem[A]. In SPIE[C],1998;191-201.
[27]张景旭,王洋.动载体光学图像视轴稳定技术[J].光电技术应用,2007,224-7.
[28]James C. Cooper sensor line of sight stabilization[A]. In SPIE[C],1991;39-50.
[29]车双良.高精度光电测控系统及其控制策略研究[D].西北工业大学2003.
[30]张晓禹.车载平台变形测量和误差校正技术的研究[D].中国科学院研究生院博士学位论文2003.
[31]Yu Q F,Jiang G W,etal. Broken-ray videometric method and system for measuringthe three-dimensional position and pose of the non-intervisible object[J]. RemoteSensing Spatial Inf Sci,2008,37145-148.
[32]张政.车载光电经纬仪在准动基座下的测量误差修正研究[D].国防科技大学硕士学位论文2007.
[33]李玉广.基于双像机的不稳定测量平台静基准转换技术研究[D].国防科学技术大学硕士学位论文2009.
[34]刘艳芳,洪炳熔.单站观测卫星初轨计算中的初值方法[J].中国空间科学技术,1999,9(12):58-65.
[35]郭福成,樊昀.空间信息对抗中的单星对卫星无源定位跟踪方法[J].宇航学报,2005,26(2):196-200.
[36]刘利生,吴斌等.航天器精确定规与自校准计术[M].北京:国防工业出版社,2005.
[37]R. C. Kolb,F. H. Hollister. Bearing-only Target Estimation[A]. In Proc of1st Asilomar Conf on Circuits and Systems[C],1967;935-946.
[38]A. G. Lindgren,K. F. Gong. Position and velocity estimation via bearingobservations[J]. IEEE Trans on AES,1978,14(4):564-577.
[39]S. E. Hammel,V. J. Aidala. Observability requirements for three-dimensionaltracking via angle measurements[J]. IEEE Trans on AES,1985,21(2):200-207.
[40]J. Levine,R. Marino. Constant-speed target tracking via bearings-onlymeasurements[J]. IEEE Trans on AES,1992,28(1):174-182.
[41]E. Fogel,M. Gavish. Nth-order dynamics target observability from anglemeasurements[J]. IEEE Transactions on Aerospace and Electronic Systems,1988,24(3):305-308.
[42]K. Becker. Simple linear theory approach to tma observability[J]. IEEE Trans onAES,1993,29(2):575-578.
[43]V. J. Aidala. Kalman filter behavior in bearings-only tracking applications[J]. IEEETrans on AES,1979,15(1):29-39.
[44]V. J. Aidala,S. C. Nardone. Biased estimation properties of the pseudolineartracking filter[J]. IEEE Trans on AES,1982,18(4):432-441.
[45]V. Aidala,S. Hammel. Utilization of modifed polar coordinates for bearings-onlytracking[J]. IEEE Trans on AES,1983,18(4):432-441.
[46]S. Nardone,A. Lindgren,etal. Fundamental properties and performance ofconventional bearings-only target motion analysis[J]. IEEE Trans on Automatic Control,1984,29(9):775-787.
[47]J. P. Helferty,D. R. Mudgett. Optimal observer trajectories for bearings onlytracking by minimizing the trace of the cramer-rao lower bound[A]. In Proceedings ofOCEANS '93'Engineering in Harmony with Ocean'[C],1993;229-234.
[48]J. A. Fawcett. Effect of course maneuvers on bearings-only range estimation[J].IEEE Trans on Acoustics, Speech, and Signal Processing,1988,36(8):1193-1199.
[49]A. Logothetis,A. Isaksson,etal. An information theoretic approach to observer pathdesign for bearings-only tracking[A]. In Proceedings of the36th IEEE Conference onDecision and Control[C],1997;3132-3137.
[50]J. P. Le Cadre. Optimization of the observer motion for bearings-only target motionanalysis[A]. In Proceedings of the36th IEEE Conference on Decision and Control[C],1997;126-131.
[51]J. E. Le Cadre,C. Jaufret. Discrete-time observability and estimability analysis forbearings-only target motion analysis[J]. IEEE Trans on AES,1997,33(1):178-201.
[52]P. T. Liu. An optimum approach in target tracking with bearing measurements[J].Journal of Optimization Theory and Applications,1988,56(2):205-214.
[53]J. M. Passerieux,D. Van Cappel. Optimal observer maneuver for bearings-onlytracking[J]. IEEE Trans on AES,1998,34(3):777-788.
[54]Y. Oshman,P. Davidson. Optimization of observer trajectories for bearings-onlytarget localization[J]. IEEE Trans on AES,1999,35(3):892-902.
[55]潘泉,戴冠中等.被动式跟踪可观测性分析的非线性系统方法[J].信息与控制,1997,26(3):168-173.
[56]G. F. Ivey,E. N. Johnson. Investigation of methods for target state estimation usingvision sensors[A]. In AIAA Guidance, Navigation, and Control Conference andExhibit[C], San Francisco, CA,2005.
[57]D. B. Barber,J. Redding,etal. Vision-based target geo-location using a fixed-wingminiature air vehicle[J]. J. Intell. Robotics Syst.,2006,47(4):361-382.
[58]F. Rafi,S. Khan,etal. Autonomous target following by unmanned aerial vehicles[A].In Proceedings of SPIE[C], Orlando,FL,2006.
[59]Sameera S. Ponda,Richard M. Kolacinskiy,etal. Trajectory Optimization for TargetLocalization Using Small Unmanned Aerial Vehicles[A]. In AIAA Guidance,Navigation, and Control Conference[C], Chicago,Illinoiis,2009.
[60]S. Avidan,A. Shashua. Trajectory Triangulation:3D Reconstruction of MovingPoints from a Monocular Image Sequence[J]. IEEE Trans On Pattern Analysis andMachine Intelligence,2000,22(4):348-357.
[61]Mei Han,Takeo Kanade. Multiple Motion Scene Reconstruction with UncalibratedCameras[J]. IEEE Trans On Pattern Analysis and Machine Intelligence,2003,25(7):884-894.
[62]F. Xu,etal. Video-object segmentation and3D-trajectory estimation for monocularvideo sequences[J]. Image Vis. Comput.,2010, doi:10.1016/j.imavis.2010.1009.1001.
[63]Robert M. Haralick,Chung-nanlee. Analysis and solutions of the three pointperspective pose estimation problem[A]. In Computer Vision and PatternRecognition[C],1991;592-598.
[64]Robert M.Haralick,Hyonam Joo,etal. Pose estimation from corresponding pointdata[J]. IEEE Transactions on Systems, Man. and Cybernetics,1989,19(6):1426-1446.
[65]Richard Hartley,Andrew Zisserman.计算机视觉中的多视图几何[M].安徽:安徽大学出版社,2002.
[66]张杰,曹喜滨等.非合作航天器间相对位姿的单目视觉确定算法[J].南京理工大学学报,2006,30(5):564-568.
[67]H.A.Martins,J.R.Birk,etal. Camera Models Based no Data from Two CalibrationPlanes[J]. Computer Graphics and Imaging Processing,1981,17173-180.
[68]F. Margaret. Perspective Projection: The Wrong Imaging Model1995.
[69]章志鸣,沈元华等.光学[M].北京:高等教育出版社,2000.
[70]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.
[71]R. Y. Tsai. A Versatile Camera Calibration Technique for High Accuracy3DMachine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses[A]. In Journalof Robotics and Automation[C],1987;323-344.
[72]J. Weng,P. Cohen,etal. Camera Calibration with Distortion Models and AccuracyEvaluation[A]. In Transactions on Pattern Analysis And Machine Intelligence[C],1992;965-980.
[73]北京凌云光视数字图像技术有限公司.图像和机器视觉产品手册.
[74]Leica TS30/TM30用户手册. http://www.leica-geosystems.com.
[75]武汉大学测绘学院测量平差学科组.误差理论与测量平差基础[M].武汉:武汉大学出版社,2002.
[76]于起峰等著.基于图像的精密测量与运动测量科学出版社:北京,2002.
[77]Lu C-P，Hager GD，Mjolsness E. Fast and Globally Convergent Pose Estimationfrom Video Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(6)610.
[78]Daniilidis K. Hand-Eye Calibration Using Dual Quaternions[J]. InternationalJournal of Robotics Research,1999,18(3):286-298.
[79]郭秀中,于波等.陀螺仪理论及应用[M].南京:航空工业出版社,1987.
[80]郭秀中.惯导系统陀螺仪理论[M].北京:国防工业出版社,1996.
[81]姚勇,张春. GPS载波相位差分技术实时测姿的研究与应用[J].中国惯性技术学报,2003,622-26.
[82]许江宁,朱涛. GPS姿态测量技术综述[J].海军工程大学学报,2003,15(3):17-22.
[83]杜春花,范胜林等.一种基于GPS的测姿新方法[J].南京航空航天大学学报,2002,34(4):394-397.
[84]欧同庚,陈志高等. CCD光电自准仪工作原理及误差源分析[J].大地测量与地球动力学,2007,2798-102.
[85]敖磊,谭久彬等.激光CCD二维自准直仪中圆目标中心精确定位算法[J].光学精密工程,2005,13(6):668-673.
[86]L.Lucchese. Closed-form pose estimation from metric rectification of coplanarpoints[A]. In IEEE Proc.-Vis. Image Signal Process[C],2006;364-378.
[87]Omar Tahri,Francois Chaumette. Complex objects pose estimation based on imagemoment invariants[A]. In Proceedings of the2005IEEE International Conference onRobotics and Automation[C], Barcelona,Spain,2005.
[88]HOMER H. CHEN. Pose determination from line-to-plane correspondences:existence condition and closed-form solutions[J]. IEEE Transactions on Patten Analysisand Machine Intelligence,1991,13(6):530-541.
[89]S. H. Or,W. S. Luk,etal. An effective iterative pose estimation algorithm[J]. Imageand Vison Computing,1998,16353-362.
[90]D.Nister,O.Naroditsky,etal. Visual Odometry[J]. IEEE Computer Vision and PatternRecognition,2004,1652-659.
[91]D.Nister. Preemptive RANSAC for live structure and motion estimation[A]. InIEEE International Conference on Computer Vision[C],2003;199-206.
[92]Long Quan,Zhongdan Lan. Linear N-Point camera pose determination[J]. IEEETrans. On Pattern Analysis and Machine Intelligence,1999,21(8):774-780.
[93]C. P. Lu, G. D. Hager, et al. Fast and globally convergent pose estimation fromvideo images[J]. IEEE Trans on Pattern Analysis and Machine Intelligence,2000,22(6):610-622.
[94]St′ephane Christy,Radu Horaud. Iterative pose computation from linecorrespondences[J]. Computer Vision and Image Understanding,1999,73(1):137-144.
[95]T. Q. Phong,R. Horaud,etal. Object pose from2-D to3-D point and linecorrespondences[J]. International Journal of Computer Vision,1995,15(3):225-243.
[96]Adnan Ansar,Kostas Daniilidis. Linear pose estimation from points or lines[J].IEEE Trans. On Pattern Analysis and Machine Intelligence,2003,25(5):578-589.
[97]Y. Liu,T. S. Huang,etal. Determination of camera location from2-D to3-D line andpoint correspondences[J]. IEEE Transactions on Patten Analysis and MachineIntelligence,1990,12(1):28-37.
[98]陈国军,孙祥一等.空间目标三维姿态的单目摄影测量[J].现代力学测试技术,1998,28(1):348-351.
[99]于起峰,孙祥一等.用光测法测量空间目标三维姿态[J].国防科技大学学报,2000,22(2):15-19.
[100]孙祥一于起峰,邱志强.从单站光测图像确定空间目标三维姿态[J].光学技术,2002.
[101]Stephens M. Harris C. A combined corner and edge detector[C][J].1988,1.
[102]D. G. Lowe. Object Recognition from Local Scale-Invariant Features[A]. InProceedings of the International Conference on Computer Vision[C],1999;1150-1151.
[103]D. G. Lowe. Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-111.
[104]Yu Q F,Jiang G W,etal. Fold-ray videometrics method for the deformationmeasurement of nonintervisible large structures[J]. Apply Optical,2009,484683-4687.
[105]王广运,郭秉义等.差分GPS技术与应用背景[M].北京:电子工业出版社,1996.
[106]程俊廷,赵灿等.基于编码结构光和外极线约束的自由曲面三维轮廓术[J].计算机测量与控制,2007,15(1):120-121.
[107]杨佳,贾书海.一种新的三维轮廓测量方法[J].光子学报,2007,36(6):973-975.
[108]郑亚红,廖金玉.逆向工程中三维曲面测量技术应用[J].沈阳工业大学学报,2006,28(4):446-470.
[109]尚洋,李立春等.摄像测量技术在国防试验与航天器对接中的应用研究[J].实验力学,2005,20(Z1):91-94.
[110]殷世民,付小宁等.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.
[111]殷世民,付小宁等.对固定平台红外单站被动定位技术研究[J].光子学报,2004,33(2):237-239.
[112]Andrew W. Fitzgibbon,Andrew Zisserman. Multibody Structure and Motion:3-DReconstruction of Independently Moving Objects[A]. In ECCV2000, LNCS1842[C],2000;891-906.
[113]庄严,王伟等.移动机器人基于激光测距和单目视觉的室内同时定位和地图构建[J].自动化学报,2005,31(6):925-933.
[114]郑元杰,杨杰.基于单摄像头双目成像系统在计算机视觉中的应用研究[J].红外与激光工程,2004,33(4):392-396.
[115]张淑芳,李华.基于一幅散焦图像的深度估计新算法[J].光电子激光,2006,17(3):364-367.
[116]李恩科,殷世民等.一种新的机动平台红外单站被动定位算法[J].西安电子科技大学学报(自然科学版)2006,33(3):408-410.
[117]S. Avidan,A. Shashua. Triangulation of lines: Reconstruction of a3D PointMoving Along a Line from a Monocular Image Sequence[A]. In Proc. IEEE Conf.Computer Vision and Pattern Recognition[C],1999.
[118]A. Shashua,S. Avidan,etal. Trajectory Triangulation Over Conic Sections[A]. InProc. Int'l Conf. Computer Vision (ICCV)[C],1999;330-337.
[119]P.R. Escobal. Methods of Orbit Determination[M]. Krieger Publishing,1976.
[2]何照才,胡保安.光学测量系统[M].北京:国防工业出版社,2002.
[3]刘利生.外弹道测量数据处理[M].北京:国防工业出版社,2002.
[4]张远新,齐国铭等.靶场机载电视经纬仪的发展和应用[J].测控技术,2002,22(4).
[5]何照才.国外靶场电影经纬仪现状[A]. In中国兵工学会第六届测试技术学会年会论文集[C],1992.
[6]张谦.星光-惯性复合制导系统[J].导弹与航天运载技术,1993,203(3):37-41.
[7]程国采.战术导弹导引方法[M].北京:国防工业出版社,2000.
[8]郭喜庆.基于机电一体化技术的新型寻北系统的研究和应用[R].中国科学院长春光学精密机械与物理研究所:2002.
[9]Yefimev MV. Ballistic Missile Aiming Systems[J]. Missile and Rockets,1970,123(4).
[10]A. L. Allan. The Principle of Theodolite Intersection Systems[J]. Survey,1988,29(277).
[11] Ailbert V. Jelalion. Laser Radar System[J]. Artech House,1992.
[12]张东梅.车载平台变形测量技术的研究[D].中国科学院研究生院博士学位论文2006.
[13]第三十一试验训练基地《训练教材》编写组.弹道测试[M].北京:国防科工委司令部教育训练部,1989.
[14]邹丕盛.现代科学技术与军事[M].北京:国防工业出版社,1998.
[15]文仲辉.战术导弹系统分析[M].北京:国防工业出版社,2000.
[16]史长捷.测控飞机站——测控技术的重要发展[J].遥测遥控,1991,12(3):1-8.
[17]苏成翔,房鸿瑞等.基于进化算法的测控飞机跟踪路径规划[J].飞行器测控学报,2009,28(1):82-84.
[18]中国科学院长春光学精密机械与物理研究所.机(舰)载电视经纬仪方案设计报告[R].中国科学院长春光学精密机械与物理研究所,2001.
[19]91550部队. XX导弹火控系统精度试验测量方案[R].2002.
[20]于起峰,尚洋.摄像测量原理与应用研究[M].北京:科学出版社,2009.
[21]牛忠文,程海平.雷达天线基准水平误差的一种测量方法[J].电子机械工程,2005,21(6):38-42.
[22]姜广文.像机链位姿传递摄像测量方法及船体变形测量研究[D].国防科技大学博士学位论文2010.
[23]万德钧,刘玉锋.消除舰船变形的影响和为全舰提供高精度姿态基准[J].中国惯性技术学报,2005,13(4):77-82.
[24]柳爱利,卢伟.甲板变形测量技术研究[J].海军航空工程学院学报,2009,24(2):178-180.
[25]张鹏.舰载摄像稳定平台的结构设计[J].舰船电子对抗,2006,2970-73.
[26]Xie. D L. Stabilization of line-of-sight for airborne O-E tracking and imagingsystem[A]. In SPIE[C],1998;191-201.
[27]张景旭,王洋.动载体光学图像视轴稳定技术[J].光电技术应用,2007,224-7.
[28]James C. Cooper sensor line of sight stabilization[A]. In SPIE[C],1991;39-50.
[29]车双良.高精度光电测控系统及其控制策略研究[D].西北工业大学2003.
[30]张晓禹.车载平台变形测量和误差校正技术的研究[D].中国科学院研究生院博士学位论文2003.
[31]Yu Q F,Jiang G W,etal. Broken-ray videometric method and system for measuringthe three-dimensional position and pose of the non-intervisible object[J]. RemoteSensing Spatial Inf Sci,2008,37145-148.
[32]张政.车载光电经纬仪在准动基座下的测量误差修正研究[D].国防科技大学硕士学位论文2007.
[33]李玉广.基于双像机的不稳定测量平台静基准转换技术研究[D].国防科学技术大学硕士学位论文2009.
[34]刘艳芳,洪炳熔.单站观测卫星初轨计算中的初值方法[J].中国空间科学技术,1999,9(12):58-65.
[35]郭福成,樊昀.空间信息对抗中的单星对卫星无源定位跟踪方法[J].宇航学报,2005,26(2):196-200.
[36]刘利生,吴斌等.航天器精确定规与自校准计术[M].北京:国防工业出版社,2005.
[37]R. C. Kolb,F. H. Hollister. Bearing-only Target Estimation[A]. In Proc of1st Asilomar Conf on Circuits and Systems[C],1967;935-946.
[38]A. G. Lindgren,K. F. Gong. Position and velocity estimation via bearingobservations[J]. IEEE Trans on AES,1978,14(4):564-577.
[39]S. E. Hammel,V. J. Aidala. Observability requirements for three-dimensionaltracking via angle measurements[J]. IEEE Trans on AES,1985,21(2):200-207.
[40]J. Levine,R. Marino. Constant-speed target tracking via bearings-onlymeasurements[J]. IEEE Trans on AES,1992,28(1):174-182.
[41]E. Fogel,M. Gavish. Nth-order dynamics target observability from anglemeasurements[J]. IEEE Transactions on Aerospace and Electronic Systems,1988,24(3):305-308.
[42]K. Becker. Simple linear theory approach to tma observability[J]. IEEE Trans onAES,1993,29(2):575-578.
[43]V. J. Aidala. Kalman filter behavior in bearings-only tracking applications[J]. IEEETrans on AES,1979,15(1):29-39.
[44]V. J. Aidala,S. C. Nardone. Biased estimation properties of the pseudolineartracking filter[J]. IEEE Trans on AES,1982,18(4):432-441.
[45]V. Aidala,S. Hammel. Utilization of modifed polar coordinates for bearings-onlytracking[J]. IEEE Trans on AES,1983,18(4):432-441.
[46]S. Nardone,A. Lindgren,etal. Fundamental properties and performance ofconventional bearings-only target motion analysis[J]. IEEE Trans on Automatic Control,1984,29(9):775-787.
[47]J. P. Helferty,D. R. Mudgett. Optimal observer trajectories for bearings onlytracking by minimizing the trace of the cramer-rao lower bound[A]. In Proceedings ofOCEANS '93'Engineering in Harmony with Ocean'[C],1993;229-234.
[48]J. A. Fawcett. Effect of course maneuvers on bearings-only range estimation[J].IEEE Trans on Acoustics, Speech, and Signal Processing,1988,36(8):1193-1199.
[49]A. Logothetis,A. Isaksson,etal. An information theoretic approach to observer pathdesign for bearings-only tracking[A]. In Proceedings of the36th IEEE Conference onDecision and Control[C],1997;3132-3137.
[50]J. P. Le Cadre. Optimization of the observer motion for bearings-only target motionanalysis[A]. In Proceedings of the36th IEEE Conference on Decision and Control[C],1997;126-131.
[51]J. E. Le Cadre,C. Jaufret. Discrete-time observability and estimability analysis forbearings-only target motion analysis[J]. IEEE Trans on AES,1997,33(1):178-201.
[52]P. T. Liu. An optimum approach in target tracking with bearing measurements[J].Journal of Optimization Theory and Applications,1988,56(2):205-214.
[53]J. M. Passerieux,D. Van Cappel. Optimal observer maneuver for bearings-onlytracking[J]. IEEE Trans on AES,1998,34(3):777-788.
[54]Y. Oshman,P. Davidson. Optimization of observer trajectories for bearings-onlytarget localization[J]. IEEE Trans on AES,1999,35(3):892-902.
[55]潘泉,戴冠中等.被动式跟踪可观测性分析的非线性系统方法[J].信息与控制,1997,26(3):168-173.
[56]G. F. Ivey,E. N. Johnson. Investigation of methods for target state estimation usingvision sensors[A]. In AIAA Guidance, Navigation, and Control Conference andExhibit[C], San Francisco, CA,2005.
[57]D. B. Barber,J. Redding,etal. Vision-based target geo-location using a fixed-wingminiature air vehicle[J]. J. Intell. Robotics Syst.,2006,47(4):361-382.
[58]F. Rafi,S. Khan,etal. Autonomous target following by unmanned aerial vehicles[A].In Proceedings of SPIE[C], Orlando,FL,2006.
[59]Sameera S. Ponda,Richard M. Kolacinskiy,etal. Trajectory Optimization for TargetLocalization Using Small Unmanned Aerial Vehicles[A]. In AIAA Guidance,Navigation, and Control Conference[C], Chicago,Illinoiis,2009.
[60]S. Avidan,A. Shashua. Trajectory Triangulation:3D Reconstruction of MovingPoints from a Monocular Image Sequence[J]. IEEE Trans On Pattern Analysis andMachine Intelligence,2000,22(4):348-357.
[61]Mei Han,Takeo Kanade. Multiple Motion Scene Reconstruction with UncalibratedCameras[J]. IEEE Trans On Pattern Analysis and Machine Intelligence,2003,25(7):884-894.
[62]F. Xu,etal. Video-object segmentation and3D-trajectory estimation for monocularvideo sequences[J]. Image Vis. Comput.,2010, doi:10.1016/j.imavis.2010.1009.1001.
[63]Robert M. Haralick,Chung-nanlee. Analysis and solutions of the three pointperspective pose estimation problem[A]. In Computer Vision and PatternRecognition[C],1991;592-598.
[64]Robert M.Haralick,Hyonam Joo,etal. Pose estimation from corresponding pointdata[J]. IEEE Transactions on Systems, Man. and Cybernetics,1989,19(6):1426-1446.
[65]Richard Hartley,Andrew Zisserman.计算机视觉中的多视图几何[M].安徽:安徽大学出版社,2002.
[66]张杰,曹喜滨等.非合作航天器间相对位姿的单目视觉确定算法[J].南京理工大学学报,2006,30(5):564-568.
[67]H.A.Martins,J.R.Birk,etal. Camera Models Based no Data from Two CalibrationPlanes[J]. Computer Graphics and Imaging Processing,1981,17173-180.
[68]F. Margaret. Perspective Projection: The Wrong Imaging Model1995.
[69]章志鸣,沈元华等.光学[M].北京:高等教育出版社,2000.
[70]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.
[71]R. Y. Tsai. A Versatile Camera Calibration Technique for High Accuracy3DMachine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses[A]. In Journalof Robotics and Automation[C],1987;323-344.
[72]J. Weng,P. Cohen,etal. Camera Calibration with Distortion Models and AccuracyEvaluation[A]. In Transactions on Pattern Analysis And Machine Intelligence[C],1992;965-980.
[73]北京凌云光视数字图像技术有限公司.图像和机器视觉产品手册.
[74]Leica TS30/TM30用户手册. http://www.leica-geosystems.com.
[75]武汉大学测绘学院测量平差学科组.误差理论与测量平差基础[M].武汉:武汉大学出版社,2002.
[76]于起峰等著.基于图像的精密测量与运动测量科学出版社:北京,2002.
[77]Lu C-P，Hager GD，Mjolsness E. Fast and Globally Convergent Pose Estimationfrom Video Images[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2000,22(6)610.
[78]Daniilidis K. Hand-Eye Calibration Using Dual Quaternions[J]. InternationalJournal of Robotics Research,1999,18(3):286-298.
[79]郭秀中,于波等.陀螺仪理论及应用[M].南京:航空工业出版社,1987.
[80]郭秀中.惯导系统陀螺仪理论[M].北京:国防工业出版社,1996.
[81]姚勇,张春. GPS载波相位差分技术实时测姿的研究与应用[J].中国惯性技术学报,2003,622-26.
[82]许江宁,朱涛. GPS姿态测量技术综述[J].海军工程大学学报,2003,15(3):17-22.
[83]杜春花,范胜林等.一种基于GPS的测姿新方法[J].南京航空航天大学学报,2002,34(4):394-397.
[84]欧同庚,陈志高等. CCD光电自准仪工作原理及误差源分析[J].大地测量与地球动力学,2007,2798-102.
[85]敖磊,谭久彬等.激光CCD二维自准直仪中圆目标中心精确定位算法[J].光学精密工程,2005,13(6):668-673.
[86]L.Lucchese. Closed-form pose estimation from metric rectification of coplanarpoints[A]. In IEEE Proc.-Vis. Image Signal Process[C],2006;364-378.
[87]Omar Tahri,Francois Chaumette. Complex objects pose estimation based on imagemoment invariants[A]. In Proceedings of the2005IEEE International Conference onRobotics and Automation[C], Barcelona,Spain,2005.
[88]HOMER H. CHEN. Pose determination from line-to-plane correspondences:existence condition and closed-form solutions[J]. IEEE Transactions on Patten Analysisand Machine Intelligence,1991,13(6):530-541.
[89]S. H. Or,W. S. Luk,etal. An effective iterative pose estimation algorithm[J]. Imageand Vison Computing,1998,16353-362.
[90]D.Nister,O.Naroditsky,etal. Visual Odometry[J]. IEEE Computer Vision and PatternRecognition,2004,1652-659.
[91]D.Nister. Preemptive RANSAC for live structure and motion estimation[A]. InIEEE International Conference on Computer Vision[C],2003;199-206.
[92]Long Quan,Zhongdan Lan. Linear N-Point camera pose determination[J]. IEEETrans. On Pattern Analysis and Machine Intelligence,1999,21(8):774-780.
[93]C. P. Lu, G. D. Hager, et al. Fast and globally convergent pose estimation fromvideo images[J]. IEEE Trans on Pattern Analysis and Machine Intelligence,2000,22(6):610-622.
[94]St′ephane Christy,Radu Horaud. Iterative pose computation from linecorrespondences[J]. Computer Vision and Image Understanding,1999,73(1):137-144.
[95]T. Q. Phong,R. Horaud,etal. Object pose from2-D to3-D point and linecorrespondences[J]. International Journal of Computer Vision,1995,15(3):225-243.
[96]Adnan Ansar,Kostas Daniilidis. Linear pose estimation from points or lines[J].IEEE Trans. On Pattern Analysis and Machine Intelligence,2003,25(5):578-589.
[97]Y. Liu,T. S. Huang,etal. Determination of camera location from2-D to3-D line andpoint correspondences[J]. IEEE Transactions on Patten Analysis and MachineIntelligence,1990,12(1):28-37.
[98]陈国军,孙祥一等.空间目标三维姿态的单目摄影测量[J].现代力学测试技术,1998,28(1):348-351.
[99]于起峰,孙祥一等.用光测法测量空间目标三维姿态[J].国防科技大学学报,2000,22(2):15-19.
[100]孙祥一于起峰,邱志强.从单站光测图像确定空间目标三维姿态[J].光学技术,2002.
[101]Stephens M. Harris C. A combined corner and edge detector[C][J].1988,1.
[102]D. G. Lowe. Object Recognition from Local Scale-Invariant Features[A]. InProceedings of the International Conference on Computer Vision[C],1999;1150-1151.
[103]D. G. Lowe. Distinctive image features from scale-invariant keypoints[J].International Journal of Computer Vision,2004,60(2):91-111.
[104]Yu Q F,Jiang G W,etal. Fold-ray videometrics method for the deformationmeasurement of nonintervisible large structures[J]. Apply Optical,2009,484683-4687.
[105]王广运,郭秉义等.差分GPS技术与应用背景[M].北京:电子工业出版社,1996.
[106]程俊廷,赵灿等.基于编码结构光和外极线约束的自由曲面三维轮廓术[J].计算机测量与控制,2007,15(1):120-121.
[107]杨佳,贾书海.一种新的三维轮廓测量方法[J].光子学报,2007,36(6):973-975.
[108]郑亚红,廖金玉.逆向工程中三维曲面测量技术应用[J].沈阳工业大学学报,2006,28(4):446-470.
[109]尚洋,李立春等.摄像测量技术在国防试验与航天器对接中的应用研究[J].实验力学,2005,20(Z1):91-94.
[110]殷世民,付小宁等.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.
[111]殷世民,付小宁等.对固定平台红外单站被动定位技术研究[J].光子学报,2004,33(2):237-239.
[112]Andrew W. Fitzgibbon,Andrew Zisserman. Multibody Structure and Motion:3-DReconstruction of Independently Moving Objects[A]. In ECCV2000, LNCS1842[C],2000;891-906.
[113]庄严,王伟等.移动机器人基于激光测距和单目视觉的室内同时定位和地图构建[J].自动化学报,2005,31(6):925-933.
[114]郑元杰,杨杰.基于单摄像头双目成像系统在计算机视觉中的应用研究[J].红外与激光工程,2004,33(4):392-396.
[115]张淑芳,李华.基于一幅散焦图像的深度估计新算法[J].光电子激光,2006,17(3):364-367.
[116]李恩科,殷世民等.一种新的机动平台红外单站被动定位算法[J].西安电子科技大学学报(自然科学版)2006,33(3):408-410.
[117]S. Avidan,A. Shashua. Triangulation of lines: Reconstruction of a3D PointMoving Along a Line from a Monocular Image Sequence[A]. In Proc. IEEE Conf.Computer Vision and Pattern Recognition[C],1999.
[118]A. Shashua,S. Avidan,etal. Trajectory Triangulation Over Conic Sections[A]. InProc. Int'l Conf. Computer Vision (ICCV)[C],1999;330-337.
[119]P.R. Escobal. Methods of Orbit Determination[M]. Krieger Publishing,1976.