面向非合作目标的自主空间飞行器图像信息处理关键技术研究
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摘要
随着空间技术的发展,交会对接、卫星服务和卫星捕获等空间飞行器近场操作活动的需求越来越多,其发展趋势是研制面向非合作目标的、不依赖外部导航设备的自主空间飞行器,因此需要研究非合作目标飞行器运动和结构信息获取技术。以此为背景,研究了面向非合作目标的、基于图像特征的信息处理方法,按信息处理任务的不同分为远距离图像信息处理和近距离图像信息处理两部分,对其中的关键技术进行了研究,提出了解决方法并设计了部分硬件电路。
远距离图像信息处理任务是进行目标飞行器的检测、识别和跟踪,研究的关键技术是弱小目标检测和面目标提取。设计了基于能量积累和轨迹关联的弱小目标检测方法,通过对能量积累后的图像进行非最大值抑制提高了检测性能;提出了基于图像灰度熵的面目标提取方法,能够完整准确地提取出图像中的目标区域。
近距离图像信息处理任务是估计非合作目标飞行器的相对运动参数和结构参数,关键技术是图像特征的提取和对应、运动与结构参数的估计。提出了Harris算子实现的硬件加速技术和改进的预存储权值矩阵Hough变换,实现了角点和直线的快速提取,设计的图像灰度直方图统计电路模块和邻域提取电路模块可以用于许多图像处理算法;提出了基于光流预测的角点和直线对应算法,通过光流预测提高了建立特征初始对应的计算效率,通过相似度判决能够得到可靠的对应;针对近距离绕飞情况,系统地提出了利用直线估计运动和结构参数的算法,包括直接线性变换算法、鲁棒性算法和光束法平差等,利用目标飞行器丰富的直线特征得到了高精度的、可靠的相对运动参数和目标结构参数。
研究成果除用于自主空间飞行器近场操作目标信息获取问题外,还可以用于其他基于角点和直线估计运动和结构参数的场合,如建筑物模型重建、移动机器人定位与导航、虚拟现实等。
With the development of space technology, proximity operations have become more and more important in many space-related applications, such as Rendezvous and Docking, Satellite Servicing, Satellite Capture, etc. The tendency is to develop autonomous spacecrafts that are independent of navigation equipments outside and targeting at non-cooperative spacecrafts. So it is necessary to study the technology of acquiring the motion and structure of non-cooperative spacecraft. Under the background, we research a method of information processing based on image features, which is targeting at non-cooperative spacecraft and has two parts for different tasks, namely far-field image information processing and near-field image information processing. Key technologies in the method are discussed and the solutions are proposed. The logic circuits of some solutions are designed and implemented.
The task of image information processing in far field is to detect, recognize and track target spacecraft. The key technologies studied in this phase are dim-small object detection and block object extraction. A detector of dim-small object is designed, which is based on energy accumulation and track association. Performance of the detector is improved through non-maximal suppression after energy accumulating. A block object detector is proposed which is based on gray entropy of image and can extract the area of the target integrally and accurately.
The task of image information processing in near field is to estimate the motion and structure of non-cooperative target spacecraft. The key technologies in this phase are features extraction, features match and structure from motion (SFM). Firstly, the logic circuits for Harris detector are demonstrated and a fast method for Hough Transform based on pre-storage weighted matrix is established. The modules of gray histography statistics and neighborhood extraction have the potential to find wide applications in various algorithms of image processing. Secondly, the algorithms of features matching based on prediction by optical flow are proposed. The efficiency of initialing correspondences is higher through motion estimation and the reliable correspondences are determined by the measures of similarity which are constructed using properties of features. Thirdly, the algorithms based on lines for SFM are proposed systematically, including directly linear transformation, robust estimation and bundle adjustment. Therefore, rich and stable line features in the target are used to estimate structure and motion with high precision and robustness while the chase spacecraft circles the non-cooperative target.
The algorithms presented in this dissertation not only have applications in proximity operations, but also show great potential in many other fields such as model reconstruction of buildings, ego-motion of robots, virtual reality, etc.
远距离图像信息处理任务是进行目标飞行器的检测、识别和跟踪,研究的关键技术是弱小目标检测和面目标提取。设计了基于能量积累和轨迹关联的弱小目标检测方法,通过对能量积累后的图像进行非最大值抑制提高了检测性能;提出了基于图像灰度熵的面目标提取方法,能够完整准确地提取出图像中的目标区域。
近距离图像信息处理任务是估计非合作目标飞行器的相对运动参数和结构参数,关键技术是图像特征的提取和对应、运动与结构参数的估计。提出了Harris算子实现的硬件加速技术和改进的预存储权值矩阵Hough变换,实现了角点和直线的快速提取,设计的图像灰度直方图统计电路模块和邻域提取电路模块可以用于许多图像处理算法;提出了基于光流预测的角点和直线对应算法,通过光流预测提高了建立特征初始对应的计算效率,通过相似度判决能够得到可靠的对应;针对近距离绕飞情况,系统地提出了利用直线估计运动和结构参数的算法,包括直接线性变换算法、鲁棒性算法和光束法平差等,利用目标飞行器丰富的直线特征得到了高精度的、可靠的相对运动参数和目标结构参数。
研究成果除用于自主空间飞行器近场操作目标信息获取问题外,还可以用于其他基于角点和直线估计运动和结构参数的场合,如建筑物模型重建、移动机器人定位与导航、虚拟现实等。
With the development of space technology, proximity operations have become more and more important in many space-related applications, such as Rendezvous and Docking, Satellite Servicing, Satellite Capture, etc. The tendency is to develop autonomous spacecrafts that are independent of navigation equipments outside and targeting at non-cooperative spacecrafts. So it is necessary to study the technology of acquiring the motion and structure of non-cooperative spacecraft. Under the background, we research a method of information processing based on image features, which is targeting at non-cooperative spacecraft and has two parts for different tasks, namely far-field image information processing and near-field image information processing. Key technologies in the method are discussed and the solutions are proposed. The logic circuits of some solutions are designed and implemented.
The task of image information processing in far field is to detect, recognize and track target spacecraft. The key technologies studied in this phase are dim-small object detection and block object extraction. A detector of dim-small object is designed, which is based on energy accumulation and track association. Performance of the detector is improved through non-maximal suppression after energy accumulating. A block object detector is proposed which is based on gray entropy of image and can extract the area of the target integrally and accurately.
The task of image information processing in near field is to estimate the motion and structure of non-cooperative target spacecraft. The key technologies in this phase are features extraction, features match and structure from motion (SFM). Firstly, the logic circuits for Harris detector are demonstrated and a fast method for Hough Transform based on pre-storage weighted matrix is established. The modules of gray histography statistics and neighborhood extraction have the potential to find wide applications in various algorithms of image processing. Secondly, the algorithms of features matching based on prediction by optical flow are proposed. The efficiency of initialing correspondences is higher through motion estimation and the reliable correspondences are determined by the measures of similarity which are constructed using properties of features. Thirdly, the algorithms based on lines for SFM are proposed systematically, including directly linear transformation, robust estimation and bundle adjustment. Therefore, rich and stable line features in the target are used to estimate structure and motion with high precision and robustness while the chase spacecraft circles the non-cooperative target.
The algorithms presented in this dissertation not only have applications in proximity operations, but also show great potential in many other fields such as model reconstruction of buildings, ego-motion of robots, virtual reality, etc.
引文
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