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A branch-and-bound algorithm applied to optimal radar search pattern

机译:一种应用于最优雷达搜索模式的分支定界算法

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In the article, the radar acquisition problem, e.g. the determination of a directional energy allocation sequence, is studied. The radar search pattern goal is the detection of a moving target whose initial location is approximately known. We have turned towards the general search theory where the observer allocates indivisible search efforts while the target presence probability spreads due to its dynamics. A few years ago, a Branch and Bound algorithm was proposed to determine the optimal sequence for a conditionally deterministic target. This operational research algorithm supposes a negative exponential detection function and a one over N detection logic, meaning that the target is declared detected if it has been detected once over a horizon of N looks. We have applied it to a narrow-beam tracking radar attempting to acquire a ballistic target. Non-trivial search patterns, such as expanding-contracting spirals, are obtained.
机译:在本文中,讨论了雷达采集问题,例如研究了定向能量分配顺序的确定。雷达搜索模式目标是检测其初始位置近似已知的移动目标。我们转向了通用搜索理论,其中观察者分配不可分割的搜索努力,而目标存在概率由于其动态而扩展。几年前,提出了一种分支定界算法来确定条件确定性目标的最佳序列。该运筹学算法假定负指数检测函数和N个以上的检测逻辑,这意味着如果在N个视域内一次检测到目标,则声明已检测到目标。我们将其应用于试图获取弹道目标的窄束跟踪雷达。获得了非平凡的搜索模式,例如伸缩螺旋。

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