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摘要: 由于地面雷达受视距限制无法对高超声速飞行器进行连续观测, 针对高超声速飞行器飞出雷达视距盲区后难以搜索的问题, 提出了一种基于信息几何的雷达搜索方法. 本文利用非参数概率密度估计法对高超声速飞行器的出现位置的概率密度进行估计, 并将估计的位置概率密度作为雷达搜索的引导信息; 根据引导信息确定搜索区域, 以区域覆盖率最大化作为优化目标在搜索区域内进行波位编排; 基于信息几何理论, 将搜索策略建模为统计流形, 利用KL (Kullback-Leibler)散度来度量搜索策略与引导信息之间的差异, 通过最小化KL散度获得最优搜索策略. 通过仿真实验验证了本文所提方法的有效性和可行性, 并验证了相比其他搜索方法具有较明显的优势.Abstract: For the limitation of the line-of-sight, the ground radar cannot continuously observe the hypersonic vehicle. To solve the problem that the hypersonic vehicle is difficult to search after flying out of the blind zone of radar line-of-sight, a search method based on information geometry is proposed. In this paper, the probability density of the occurrence position of hypersonic vehicle is estimated based on the nonparametric probability density estimation method, and the estimated position probability density is used as the guidance information for radar search. According to the guidance information the search area is determined, and the beam position arrangement is carried out in the search area with the maximization of regional coverage as the optimization goal. Based on the theory of information geometry, the search strategy is modeled as a statistical manifold. The difference between the search strategy and the guidance information is measured by the Kullback-Leibler (KL) divergence. The optimal search strategy is solved by minimizing the KL divergence. The effectiveness and feasibility of the proposed method are verified by simulation experiments, and it is proved that it has obvious advantages over other search strategies.
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表 1 雷达参数
Table 1 Radar parameters
参数 值 探测距离 (km) 2000 测角误差 (°) 0.2 测距误差 (m) 100 方位角覆盖范围 (°) −75 ~ +75 俯仰角覆盖范围 (°) 0 ~ 70 波束宽度 (°) 1×1 波束驻留时间 (ms) 100 检测概率 80% 表 2 仿真结果对比
Table 2 Comparison of simulation results
方法 波位编排方式 搜索波位个数 捕获概率 (%) 本文所提方法 优化 6.2 78 未优化 7.5 76 基于信息论的搜索方法 优化 7.3 39 未优化 7.8 40 传统搜索方法 平行搜索 优化 9.6 45 未优化 10.2 45 随机搜索 优化 8.5 55 未优化 8.9 53 螺旋搜索 优化 9.1 46 未优化 9.5 46 -
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