摘要
随着新军事变革的不断深化，空间已成为战略竞争新的制高点，空间安全成为国家安全与发展的基石。空间操作技术是保障空间安全的重要基础能力之一，在空间计划和任务中扮演着越来越重要的角色。目标航天器相对于追踪航天器的位置和姿态参数（位姿参数）的测量是多数空间操作任务中必不可少的关键环节，单目视觉是实现该测量过程的重要手段之一，在近距离范围更是首选的测量手段，因而需要对基于单目视觉的空间目标位姿测量技术进行深入的研究。
本文以空间操作任务中近距离段的目标相对位姿信息获取问题为背景，对基于单目视觉系统对空间目标进行位姿测量的方法进行研究，以进一步提高空间目标位姿测量的速度、精度、鲁棒性和适应能力。论文避开了图像预处理和特征提取等受实际系统和目标特性影响较大的问题，着力解决基于特征点求解目标位姿的算法层面的问题，主要研究内容如下：
（1）对正交迭代算法（OI算法）进行了深入研究，提出了一种改进的实现形式，并针对平面目标引起的位姿模糊问题提出了新的解决方法。改进的算法通过调整计算公式减少运算过程中的冗余，并在初始位姿求解过程中用平行透视模型取代弱透视模型，不仅大幅度提高了位姿求解的速度，还进一步提高了其稳定性和收敛性能。对于平面目标引起的位姿模糊问题，通过以平行透视模型下的两个局部最优位姿分别作为初始值进行正交迭代优化，提出了一种新的解决方法，较现有的同类算法减少了一次正交迭代优化过程，大幅度提高了运算效率。
（2）对平行透视迭代算法（PI算法）进行了深入研究，并对其进行了多方面改进。针对PI算法因需要特殊的投影参考点而性能会受到目标点空间分布状态影响的问题，通过巧妙使用齐次坐标消除了对参考点的依赖，同时改善了算法的收敛性能和精度。PI算法虽然提供了解决位姿模糊问题的方法，但在迭代过程中需要花费大量的时间对中间解进行选择，改进算法提出了一种中间解快速选择策略，并解决了原算法计算过程中的一处数值问题，明显提高了平面目标位姿求解的速度和稳定性。
（3）提出了一种基于平行透视模型的同时位姿估计与对应确定算法（SoftPI算法）。通过将平行透视模型引入同时位姿估计与对应确定问题的求解，并参考SoftPOSIT算法的思路，得到了一种新的算法，在与SoftPOSIT算法精度相当的前提下，具有更强的局部搜索能力和更高的运算效率。此外，通过应用本文提出的中间解快速选择策略，SoftPI算法还可以解决位姿模糊问题，在同类算法中首次具备了处理平面目标的能力。
（4）提出了一种基于差分进化的同时位姿估计与对应确定算法（DePose算法）。SoftPI和SoftPOSIT算法的全局搜索能力较差，更适合于已知一定位姿范围时的同时位姿估计与对应确定问题求解。对于位姿信息完全未知的情况，本文通过引入差分进化算法并提出一种新的差分进化机制和越界参数处理方法，得到了一种更好的解决方案。实验数据表明，DePose算法不仅相比现有基于遗传算法的解决方案具有更高的运算效率和更强的全局搜索性能，而且其局部搜索性能超过了SoftPI算法。
研究成果除可以为空间机动平台在天基背景下实时获取目标的近距/超近距形态信息提供技术支撑外，还很容易推广到视觉伺服、移动机器人定位与导航和虚拟现实等其它应用领域。
With the increasing deepening of a new revolution in military affairs, the space has be-come the new commanding elevation of strategic competition, and the space security has be-comethecornerstoneofacountry’ssecurityanddevelopment. Thespaceoperationtechnologyisoneofthevital basic capacitiesforprotectingthespacesecurity, which playsanincreasinglyimportantroleinthespaceprogramandmission. Themeasurementoftherelativepositionandattitude parameters (pose parameters) from the target spacecraft to the tracking spacecraft isa key essential step of most space operation tasks. Monocular vision is one of the significantmethods to achieve the measurement process, which is the preferred means of measurementat close range. Therefore, it is necessary to do more in-depth research on space object posemeasurement technique based on monocular vision.
The background of this paper is based on the obtaining of relative pose information of thetargetincloserangesegmentofthespaceoperationtasks. Itstudiesthemethodsofspaceobjectpose measurement based on the monocular vision system. The target of the study is to explorehow to improve the speed, accuracy, robustness and the adaptation capacity of space objectpose measurement. This paper avoids the problems such as image pre-processing and featureextraction which are closely related with the actual system and the target characteristics. Onthe contrary, it makes efforts to solve the problem of solving the object pose based on featurepoints on the algorithmic level. The main contents of the study are listed as follows:
(1) It explores the Orthogonal iterative (OI) algorithm in depth, raises a improved real-ization form of the OI algorithm, and it proposes a new solution of the pose ambiguity causedby the planar targets. The improvement is realized by means of adjustment formula to reducecalculational redundancy, and of adopting paraperspective model instead of weak perspectiveduring the initial pose solution process. This method not only greatly improves the speed ofposition solution, but also further improves its stability and convergence performance. Thisstudyraisesanewsolutiontosolvetheposeambiguitycausedbytheplanartargets,whichisre-alized by the iterative optimization using the two local optimal pose under the paraperspectivemodel as the initial value. It works out a new resolvent, which is less an orthogonal iterativeoptimizationprocesscomparedwithexistingsimilaralgorithmandwhichgreatlyimprovestheefficiency of operations.
（2）It studies the paraperspective (PI) iteration algorithm in-depth and it makes a lotof improvement on the PI algorithm. The performance of PI algorithm will be affected by the space distribution of the target state because it needs a special projection reference point. Thisstudy focuses on this problem and improves the convergence performance and accuracy of thePI algorithm through clever use of homogeneous coordinates to eliminate the dependence ofthe reference point. Although the PI algorithm provides a method to solve the pose ambiguity,it still takes a lot of time to choose the intermediate solutions in an iterative process. Theimproved algorithm proposed an intermediate solution fast selection strategy, and it solves anumerical problem in the original algorithm calculation process, which obviously improvesthe speed and stability to the pose solution of planar targets.
（3）The study proposes a simultaneous pose estimation and correspondence determina-tion algorithm based on the paraperspective model (SoftPI). It works out a new algorithm byintroducing the paraperspective model into simultaneous pose estimation and correspondencedetermination solution, referencing the way of SoftPOSIT algorithm. The new algorithm hasa stronger local search ability and higher operation efficiency, on the premise of the similaraccuracy with the SoftPOSIT algorithm. Moreover, SoftPI algorithm could also solve the poseambiguity by applying the intermediate solution fast selection strategy raised in this paper. Itis the first time that an algorithm of the same kind has the ability to deal with a planar target.
（4）This study proposes a simultaneous pose estimation and correspondence determi-nation algorithm based on differential evolution (DePose). SoftPI and SoftPOSIT have a poorglobal searching ability, which are more suitable for solving simultaneous pose estimation andcorrespondence determination problems with a known pose range. In the condition that thepose information is totally unknown, this study raises a better solution by introducing the dif-ferential evolution algorithm and proposing a new differential evolution mechanism and theover boundary parameter processing method. The research results indicates that the DePosealgorithm not only has higher computing efficiency and stronger performance of global searchthantheexistinggeneticalgorithmbasedsolution,butalsohashigherlocalsearchperformancethan SoftPI algorithm.
It is aimed that the research findings of this study provides technical support to the spacemobile platforms for real-time accessing the short-range/close short-range morphological in-formation of the target in space. It is also quite easy to be promoted in other application fieldssuch as visual servo, mobile robot localization and navigation, and virtual reality.
引文
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