Through the analysis of window tracking algorithm which is usually based in static background, a solution is proposed to apply the algorithm to the condition of dynamic-background.
本文通过分析几种现有的静止背景下的波门跟踪算法的基本原理，提出了其在运动背景下的对运动目标的跟踪方案；
For the problem of passive location under low detection probability, a multi-sensor fusion tracking algorithm based on sliding window batch technique is presented.
针对低检测概率下的无源定位问题，提出一种基于滑窗批处理的多传感器融合跟踪算法。
Through the trajectory tracking of a planar 3-dof robot and the simulation examples of 8d-wmm implementation window, the algorithm feasibility is validated.
并通过平面3自由度机器人轨迹跟踪和8d -WMM执行窗口作业的仿真实例，验证了算法的可行性。
After preprocessing the sampled real-time image sequences, moving target tracking is realized by combining improved Ostu algorithm and adaptive window tracing method.
在对采集的实时序列图像进行滤波处理后，本文通过改进最大类间方差法，并将其和自适应波门跟踪方法结合起来实现运动目标的跟踪。
After preprocessing the sampled real-time image sequences, moving target tracking is realized by combining improved Ostu algorithm and adaptive window tracing method.
在对采集的实时序列图像进行滤波处理后，本文通过改进最大类间方差法，并将其和自适应波门跟踪方法结合起来实现运动目标的跟踪。
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