方位角预测目标跟踪系统的研究

Research on Azimuth Prediction of Target Tracking System 

摘要:

为了实现目标被遮挡条件下的自动预测跟踪,研究了跟踪机动目标过程中的自适应卡尔曼预测算法,建立了目标遮挡预测跟踪测试系统;首先,根据算法推导了导引头方位角位置预测方法,接着,测试对比了自适应预测算法采样周期对预测精度的影响,最后,设计多种不同的目标运动形式,并通过转台实现,测试自适应算法在典型测试条件下的有效性和准确程度;实验结果表明:目标被遮挡时,预测角增量指令相比图像角增量跟踪指令降低67%;仅需要导引头框架的角位置数据,无须脱靶量数据和弹目距离,满足遮挡条件下目标预测跟踪的功能要求。

Abstract:

In order to solve the problem that how a sheltered target is predicted and tracked, adaptive kalman prediction algorithms are presented and a test platform is setup. First, gimbals angle prediction algorithms are deduced according to adaptive kalman filter algorithms based on current accelerate mode. Second, sampling period selection in the adaptive prediction algorithms is studied. Finally, experiments are executed to verify the correctness and precision in the condition that several different target motion situations are designed and carried out on the two-axes revolving table. It is concluded that the command from prediction is decreased by 67%. Angular position data only needs seeker framework, without off-target bombs target distance and the amount of data to meet the target under occlusion conditions forecast track functional requirements.