靶场图像目标检测跟踪与定姿技术研究
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摘要
光学测量技术是靶场测控技术的重要组成部分。通过判读光测设备拍摄的图像可得到飞行目标外弹道及姿态等参数,这些参数是武器试验鉴定及故障分析的重要依据。本文以靶场光测图像自动判读工作为背景,研究了运动目标的自动检测跟踪与三维姿态测量等技术,并将其成功应用于靶场光测图像判读系统中,提高了图像判读的可靠性与效率。论文主要研究成果如下:
1.针对靶场目标多为已知目标的特点,提出了两种单样本训练的目标检测方法:①基于方向核形态滤波的目标检测方法,该方法充分利用了图像核特征的稳定性,对靶场复杂背景图像的目标检测具有很强的适应性。②基于形状熵差的目标检测方法,该方法根据样本图像中目标的形状特征构造形状熵差目标检测算子,能够有效地用于靶场多目标图像的自动目标检测。这些方法在仅提取单个目标样本图像特征的情况下,实现了鲁棒的目标检测。
2.针对靶场序列图像目标稳定跟踪问题,提出了三种目标跟踪方法:①基于梯度LoG算子的光团目标跟踪方法,该方法具有检测精度高、对环境光照变化适应性强等优点,能够稳定跟踪靶场图像中的光团小目标。②基于特征点匹配的跟踪漂移校正方法,该方法可与多种跟踪算法相结合,对跟踪结果进行跟踪漂移检测,然后根据需要进行漂移校正。③一种多视约束下基于点描述的多目标跟踪匹配方法,该方法将多视约束关系融入到单站序列图像目标二维轨迹分析中,能够较好地解决多站序列图像间多目标跟踪匹配问题。
3.针对靶场图像中弹体小目标中轴线的提取问题,提出了一种基于迭代矩的中轴线提取算法,该算法通过迭代不断改进矩方法的计算区域,最大限度地抑制了背景干扰,实现了目标中轴线的高精度提取。此外,本文定量地分析了中轴线面面交会法的误差影响因素,并给出了误差模型。
4.结合光测设备成像模型与目标自身结构特点,提出了两种三维姿态参数解算方法:①利用离轴结构线求解目标滚转角的方法,该方法能够十分方便地测量飞机、巡航导弹等常见目标的滚转角。②基于目标比例信息的单站图像定姿方法,在近似平行投影成像条件下,可以不考虑目标位置和像机焦距等因素直接计算目标姿态,能够较好地满足靶场单站光测设备的定姿需求。
5.针对靶场数字图像判读的需求,设计了靶场通用数字图像判读系统的总体方案,分析并实现了系统构建所需的几项关键技术:红外图像增强技术、异源图像目标判读点分析技术、多站图像并行判读技术、运动目标检测跟踪与定姿方法在目标判读系统中的应用等。
将本文研究内容作为光测图像判读系统的关键技术之一,与靶场图像事后处理的其他技术相结合,设计并实现了一套通用的靶场数字图像判读系统,已应用于海军、空军以及总装备部所属各靶场。
Optical measurement technique is an important component of measurement and control technology in shooting ranges. The ballistic trajectory and pose parameters of the flight object, which are the significant evidences for the assessment of weapon test and the analysis of failure, can be obtained by interpreting the images captured by the optical measurement equipments. The automatic interpretation of the images captured by the optical measurement equipments is taken as the background of this dissertation. The automatic target detection, tracking and three Dimensional(3-D) pose measurement are investigated and applied successfully to the interpretation system of the images, which improve the reliability and efficiency of image interpretation. The main contents and contribution of this dissertation are as follows:
1. As the information of targets in shooting range is mostly known, two robust methods based on single example training for target detection are proposed as follows:①Target detection method based on steering kernel morphological filter of single example, which makes full use of the stability of steering kernel description and is suitable for target detection in complex background.②Target detection method for similar multi-target detection based on shape entropy difference, the shape entropy difference operator is designed by specific shape of target, which can be used to detect small targets in multi-target images of shooting range.
2. In order to track the target stably, three methods for stable tracking are proposed, they are as follows:①A new small target tracking method based on the gradient Laplacian of Gaussian(LoG) operator, which has the high precision of target detection and is robust to the change of illumination.②A drift correction method based on feature points matching, which can be combined with many tracking methods to address the problem of drift. The tracking result is checked frame by frame and drift correction is applied if necessary.③A new method based on point description for multi-target tracking with multi-view constraint. The constraint of multi-view is utilized to analyze the trajectories of targets in image sequence, and the algorithm is very suitable for tracking multi-targets in shooting range.
3. To extract the axis of small target in image of shooting range, an iterative moment method for extracting target’s axis is proposed, the iteration process is designed to improve the fit region of target, which can restrain the interference of background obviously, therefore the high-precision result of extraction is obtained. In addition, the influencing factor and error of the axes method is analyzed quantificationally.
4. By using the imaging model and target’s structure, two methods for pose estimation are proposed. They are as follows:①New convenient method for measuring rolling angle by axis and off-axis lines of targets, which can be applied to determine the rolling angle of targets such as plane and cruise missile.②New method for measuring the pose of target with known structure based on proportions of feature points, which can determine the 3-D pose from mono-view. Under the parallel projection imaging model, the pose of object can be directly calculated without target’s 3-D position and camera parameter such as focus length.
5. Considering the requirements of digital image interpretation, a design scheme for universal digital image interpretation system is proposed. Meanwhile, several key technologies are discussed for constructing the image interpretation system, i.e., infrared image enhancement techniques, analysis of targets’interpretation position from multi-sensor images, parallel interpreting images from different cameras, applications of target detection, tracking and 3-D pose measurement in image interpretation system.
The technologies researched and other related technologies for image interpretation are utilized to realize a digital image interpretation system, and the system has been playing an important role in images interpretation of shooting ranges of Navy, Air Force and Gerneral Armament Department.
1.针对靶场目标多为已知目标的特点,提出了两种单样本训练的目标检测方法:①基于方向核形态滤波的目标检测方法,该方法充分利用了图像核特征的稳定性,对靶场复杂背景图像的目标检测具有很强的适应性。②基于形状熵差的目标检测方法,该方法根据样本图像中目标的形状特征构造形状熵差目标检测算子,能够有效地用于靶场多目标图像的自动目标检测。这些方法在仅提取单个目标样本图像特征的情况下,实现了鲁棒的目标检测。
2.针对靶场序列图像目标稳定跟踪问题,提出了三种目标跟踪方法:①基于梯度LoG算子的光团目标跟踪方法,该方法具有检测精度高、对环境光照变化适应性强等优点,能够稳定跟踪靶场图像中的光团小目标。②基于特征点匹配的跟踪漂移校正方法,该方法可与多种跟踪算法相结合,对跟踪结果进行跟踪漂移检测,然后根据需要进行漂移校正。③一种多视约束下基于点描述的多目标跟踪匹配方法,该方法将多视约束关系融入到单站序列图像目标二维轨迹分析中,能够较好地解决多站序列图像间多目标跟踪匹配问题。
3.针对靶场图像中弹体小目标中轴线的提取问题,提出了一种基于迭代矩的中轴线提取算法,该算法通过迭代不断改进矩方法的计算区域,最大限度地抑制了背景干扰,实现了目标中轴线的高精度提取。此外,本文定量地分析了中轴线面面交会法的误差影响因素,并给出了误差模型。
4.结合光测设备成像模型与目标自身结构特点,提出了两种三维姿态参数解算方法:①利用离轴结构线求解目标滚转角的方法,该方法能够十分方便地测量飞机、巡航导弹等常见目标的滚转角。②基于目标比例信息的单站图像定姿方法,在近似平行投影成像条件下,可以不考虑目标位置和像机焦距等因素直接计算目标姿态,能够较好地满足靶场单站光测设备的定姿需求。
5.针对靶场数字图像判读的需求,设计了靶场通用数字图像判读系统的总体方案,分析并实现了系统构建所需的几项关键技术:红外图像增强技术、异源图像目标判读点分析技术、多站图像并行判读技术、运动目标检测跟踪与定姿方法在目标判读系统中的应用等。
将本文研究内容作为光测图像判读系统的关键技术之一,与靶场图像事后处理的其他技术相结合,设计并实现了一套通用的靶场数字图像判读系统,已应用于海军、空军以及总装备部所属各靶场。
Optical measurement technique is an important component of measurement and control technology in shooting ranges. The ballistic trajectory and pose parameters of the flight object, which are the significant evidences for the assessment of weapon test and the analysis of failure, can be obtained by interpreting the images captured by the optical measurement equipments. The automatic interpretation of the images captured by the optical measurement equipments is taken as the background of this dissertation. The automatic target detection, tracking and three Dimensional(3-D) pose measurement are investigated and applied successfully to the interpretation system of the images, which improve the reliability and efficiency of image interpretation. The main contents and contribution of this dissertation are as follows:
1. As the information of targets in shooting range is mostly known, two robust methods based on single example training for target detection are proposed as follows:①Target detection method based on steering kernel morphological filter of single example, which makes full use of the stability of steering kernel description and is suitable for target detection in complex background.②Target detection method for similar multi-target detection based on shape entropy difference, the shape entropy difference operator is designed by specific shape of target, which can be used to detect small targets in multi-target images of shooting range.
2. In order to track the target stably, three methods for stable tracking are proposed, they are as follows:①A new small target tracking method based on the gradient Laplacian of Gaussian(LoG) operator, which has the high precision of target detection and is robust to the change of illumination.②A drift correction method based on feature points matching, which can be combined with many tracking methods to address the problem of drift. The tracking result is checked frame by frame and drift correction is applied if necessary.③A new method based on point description for multi-target tracking with multi-view constraint. The constraint of multi-view is utilized to analyze the trajectories of targets in image sequence, and the algorithm is very suitable for tracking multi-targets in shooting range.
3. To extract the axis of small target in image of shooting range, an iterative moment method for extracting target’s axis is proposed, the iteration process is designed to improve the fit region of target, which can restrain the interference of background obviously, therefore the high-precision result of extraction is obtained. In addition, the influencing factor and error of the axes method is analyzed quantificationally.
4. By using the imaging model and target’s structure, two methods for pose estimation are proposed. They are as follows:①New convenient method for measuring rolling angle by axis and off-axis lines of targets, which can be applied to determine the rolling angle of targets such as plane and cruise missile.②New method for measuring the pose of target with known structure based on proportions of feature points, which can determine the 3-D pose from mono-view. Under the parallel projection imaging model, the pose of object can be directly calculated without target’s 3-D position and camera parameter such as focus length.
5. Considering the requirements of digital image interpretation, a design scheme for universal digital image interpretation system is proposed. Meanwhile, several key technologies are discussed for constructing the image interpretation system, i.e., infrared image enhancement techniques, analysis of targets’interpretation position from multi-sensor images, parallel interpreting images from different cameras, applications of target detection, tracking and 3-D pose measurement in image interpretation system.
The technologies researched and other related technologies for image interpretation are utilized to realize a digital image interpretation system, and the system has been playing an important role in images interpretation of shooting ranges of Navy, Air Force and Gerneral Armament Department.
引文
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