当运动目标相互遮挡时，在卡尔曼滤波器预测区域内采用交叉搜索法实现多个运动目标的精确匹配。
When a dynamic occlusion occurred between two or more objects, the accurate matching of several moving objects could be obtained by using cross search method in the forecast area of Kalman filter.
提出了一种采用卡尔曼滤波器作为杂波背景预测器的小目标检测方法。
A small target detection method using Kalman filter as the clutter background prediction was presented.
提出了一种基于卡尔曼滤波器预测理论的容延迟移动传感器网络路由协议。
An adaptive routing based on Kalman filter prediction theory for DTMSN was raised.
为了提高系统图像处理速度，利用卡尔曼滤波器对跟踪的特征点进行预测，并用窗口处理技术减小图像处理区域。
In order to improve the speed of image processing, the Kalman filter is used to predict the next place of tracked point.
卡尔曼滤波器和预测器正符合上述要求。
该无源被动定位系统采用了加权最小二乘法来估计目标位置并用卡尔曼滤波器对目标进行跟踪与预测。
Weighted least square estimation for target location and Kalman filtering for tracking and predication are used in such passive location system.
然后将目标跟踪技术应用于特征点的跟踪，利用两个一维卡尔曼滤波器分别对特征点的两个坐标进行预测跟踪。
Then the object tracking technique is introduced into the tracking of feature points, using two 1d Kalman filter to track the two coordinates of feature points.
然后将目标跟踪技术应用于特征点的跟踪，利用两个一维卡尔曼滤波器分别对特征点的两个坐标进行预测跟踪。
Then the object tracking technique is introduced into the tracking of feature points, using two 1d Kalman filter to track the two coordinates of feature points.
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