随机入场引导
Stochastic Entry Guidance
摘要：
在本文中，闭环进入制导在一个随机扰动的大气中，使用倾斜角控制，提出了作为一个随机最优控制问题。进入弹道，以及闭环控制，都被建模为随机过程与统计数据确定的进入动力学，进入指导，和概率结构的高度相关的大气密度变化。进入制导，这是参数化的线性反馈增益序列，被设计成引导的概率分布的进入轨迹，同时满足上的允许的控制输入和最大允许的状态误差的界限。火星进入方案的数值模拟表明，改进的范围瞄准性能与约50%，降低第一和第99百分位数的最终距离误差时，使用开发的随机制导方案相比，现有的阿波罗最后阶段算法。
英文摘要：
In this paper, closed-loop entry guidance in a randomly perturbed atmosphere, using bank angle control, is posed as a stochastic optimal control problem. The entry trajectory, as well as the closed-loop controls, are both modeled as random processes with statistics determined by the entry dynamics, the entry guidance, and the probabilistic structure of altitude-dependent atmospheric density variations. The entry guidance, which is parameterized as a sequence of linear feedback gains, is designed to steer the probability distribution of the entry trajectories while satisfying bounds on the allowable control inputs and on the maximum allowable state errors. Numerical simulations of a Mars entry scenario demonstrate improved range targeting performance with approximately 50% lower 1st and 99th percentile final range errors when using the developed stochastic guidance scheme as compared to the existing Apollo final phase algorithm.
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