摘要
在目标被遮挡条件下的自动预测跟踪中,研究了跟踪机动目标过程中的角位置自适应卡尔曼预测算法。针对估计与预算中出现的发散现象,推导了导引头框架角位置预测方法。建立了目标遮挡预测跟踪测试系统,设计多种不同的目标运动形式,并通过转台实现,测试改进的自适应位置预测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:当目标进入遮挡区域时,改进的自适应位置预测算法能够有效地实现预测跟踪,保证目标退出遮挡时能够顺利重新捕获和跟踪。
In automatic forecasting and tracking of a sheltered target, how to solve the problem of missing the target shortly has been a hot research. For the divergence phenomenon appears in estimation and budget,gimbals angle prediction algorithms are deduced according to adaptive Kalman filter algorithms based on current accelerate mode. A test platform is setup. Experiments are executed to verify the correctness and precision in the condition that several dif erent target motion situations are designed and carried out on the two-axes revolving table. It is concluded that the prediction algorithms can work ef ectively while the target is sheltered and the target can be recaptured and tracked immediately after the shelter disappears.
