为解决高超声速飞行器俯冲段载荷抛撒问题,提出了基于抛撒点弹道参数组合与载荷落点映射关系的高精度载荷抛撒制导方法.采用人工神经网络方法建立了抛撒点弹道参数组合与载荷落点的映射关系,极大地降低了存储量并且提高了在线计算效率.在建立的映射关系基础上,通过设计飞行器向固定点、固定状态导引的制导律,给出了抛撒点固定的载荷抛撒制导方法;为了提高载荷抛撒的灵活性,采用预测-校正思想,给出了抛撒点实时确定的预测-校正载荷抛撒制导方法.CAV-H飞行器的载荷抛撒制导仿真表明,2种载荷抛撒制导方法获得的落点精度分别为300m与17m,所提出的2种制导方法涵盖了载荷抛撒制导的2类主要方案,可互为重要补充,能够为高超声速飞行器俯冲段高精度载荷抛撒提供参考.%To solve the load ejection problem in dive phase of hypersonic vehicle,the high-precision load ejection guidance method based on the mapping between trajectory parameters of ejection point and load fall point was proposed,and the mapping was established by using artificial neural network,which can reduce the storage and improve the online computation efficiency remarkably.By means of the design of guidance law guiding vehicle to fixed point and fixed states,a guidance approach for load ejection with fixed ejection point was presented.A load ejection guidance algorithm with choosing the ejection point in real time was developed by using predictor-corrector principle to improve the flexibility of load ejection.The results of CAV-H vehicle guidance test show that the miss distances of the two load ejection guidance methods are 300 m and 17 m respectively.The proposed guidance methods cover both of the two main load ejection guidance schemes,which complement each other.The guidance methods offer reference for high-precision load ejection of hypersonic vehicle in dive phase.
展开▼
