摘要
构建了一个以无人飞行器为载体的基于视觉的低空跟踪系统。该系统由地面站和机载模块两部分组成,构建了机载自动跟踪与地面人工干预两个并联的控制回路;采用了基于灰度直方图的自适应容忍度多阈值分割算法,并在此基础上采用了基于双重子窗口的动态聚类目标提取方法;用目标的形心脱靶量作为云台的控制参数,根据目标的运动趋势对速度参数进行调整。系统通过用鼠标对监控视野中心的坐标替换目标的形心脱靶量实现机载自动跟踪和地面人工干预的平滑切换;保留不同照度下目标的灰度阈值,使得运动区域在阴影下也能被分割。经过2～3次的聚类迭代,较精确地计算出目标的形心位置,排除了干扰目标的影响,系统的处理速度达到15 frame/s。结果表明,上述算法和方法是可行的,系统具有较大的实用性。
A vision-based low altitude tracking system mounted on an unmanned aerial vehicle is established. The system is composed of ground station and on-board module, and constructed two parallel control loops： automatic tracking control loop and manual intervening control loop. The multi-threshold segmentation algorithm with adaptive tolerance based on gray-level histogram is presented,and a object dynamic clustering algorithm with double sub-windows is analyzed. The pan and tilt head are controlled based on the miss distance of the object centroid. The system can switch smoothly from one control loop to another as the miss distance is replaced by the coordinates of the mouse relative to the center of the monitor view. The motion is segmented even in the shade by several appended thresholds for varying illunination. The object centroid position is obtained correctly through 2～3 iterations in the process of dynamic clustering, and the disturbance of other objects is removed. The system can produce good tracking results at a frame rate of 15 frame/s. The results show that the algorithms and methods are available, and the system has a certain extent practicability.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2007年第6期957-965,共9页
Optics and Precision Engineering
基金
上海市科学技术委员会国际合作项目(No.045107031)
教育部高等学校重点学科建设项目(No.Y0102)
上海市重点学科建设项目(No.BB67)
关键词
低空跟踪
并联控制回路
多阈值分割算法
双重子窗口
动态聚类
脱靶量
low altitude tracking
parallel control loop
multi-threshold segmentation algorithm^double sub-windows
dynamic clustering
miss distance
