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Optimal Intercept Missile Guidance Strategies with Autopilot Lag

机译:具有自动驾驶滞后的最优拦截导弹制导策略

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In the linear-quadratic pursuit-evasion game, the pursuer (interceptor) wishes to minimize the terminal miss,nwhereas the evader (target)wishes tomaximize it.Therefore, the optimal strategy of the interceptor is derived againstnthe anticipatedworst possible strategy of the target. If the interceptor has a lag, the current approach is to include thisnlag directly in the system dynamics, which are known to both players. In this problem formulation, the optimal costncould easily go to infinity, which means that the target will win the game. This is expected, because the target hasnknowledge about interceptor’s lag. To ensure the existence of an interceptor strategy, the weighting on the terminalnmiss has to be chosen small enough so that the optimal cost will remain finite. However, this manipulation preventsnthe target from maximizing the terminal miss and effectively constrains the target strategy. Therefore, theninterceptor strategy is derived against theworst-case target strategy that is not really theworst case. In this paper, it isnshown that this interceptor strategy performs poorly in realistic situations where the target tries to maximize thenterminal miss. Instead, two new interceptor strategies are derived against target strategies that are determinednwithout knowledge about the interceptor’s lag. These two optimal interceptor strategies improve the game-theoreticnguidance law for homing missiles by correctly taking into account the autopilot lag.
机译:在线性二次追逃游戏中,追赶者(拦截者)希望最大程度地减少终端失误,而逃避者(目标)则希望将其最大化。因此,拦截器的最佳策略是针对预期的最差目标而得出的。如果拦截器有滞后,则当前方法是将此滞后直接包括在两个参与者都知道的系统动力学中。在这个问题的表述中,最优成本很容易变成无限,这意味着目标将赢得比赛。这是预料之中的,因为目标对拦截器的滞后有所了解。为了确保存在拦截器策略,必须对终端信号的权重选择得足够小,以使最优成本保持有限。但是,这种操作会阻止目标最大化终端未命中,并有效地限制了目标策略。因此,针对最坏情况的目标策略(并非真正最坏的情况)得出拦截器策略。在本文中,没有显示这种拦截器策略在目标试图最大程度地提高终端未命中率的现实情况下效果不佳。取而代之的是,针对在不了解拦截器滞后知识的情况下确定的目标策略派生出两种新的拦截器策略。通过正确考虑自动驾驶仪的滞后,这两种最佳拦截器策略改善了用于制导导弹的游戏理论指导律。

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