摘要
在应用云台带动摄像头进行目标跟踪的过程中,由于摄像头的图像拍摄机理及采集延时、处理延时和云台转动缓慢等原因,都可能使控制装置无法及时跟踪目标,使得运动目标不能处在摄像头的最佳观测位置,由此产生目标跟踪失效。本文提出卡尔曼预测跟踪模型,给出卡尔曼滤波算法,充分利用卡尔曼滤波的递推估计能力对目标位置进行预测,最后仿真结果证实了该方法的正确性。
In the process of tracking targets using a pickup camera, because of the pickup camera＇s photography mechanism and the gathering time delay, the processing time delay and the pan-tilt＇ speed, all these reasons will possibly cause the control device to be unable promptly to track the target, and the moving goal will not be in the best observation position of the pickup camera. The result of this is the target tracking expiration. This article brings forward the Kalman filter tracking model to predict the moving object, fully using the the Kalman filter＇s recursion capacity to estimate the target location of the next time, the final simulation result confirmed the accuracy of this method.
出处
《国外电子测量技术》
2006年第10期53-55,共3页
Foreign Electronic Measurement Technology
关键词
卡尔曼滤波
目标跟踪
云台
Kalman filter, tracking target, pan-tilt
