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目标运动参数未知给移动目标优化搜索问题带来不确定性,制约了优化搜索计划的制定、降低了侦察监视资源的使用效益.为了降低目标运动引入的不确定性影响和辅助目标优化搜索计划的制定,针对大地坐标系下目标运动预测问题,首先在平面笛卡尔坐标系下对目标的运动进行分析,推导出一种基于高斯分布的目标转移概率密度函数;然后在三维笛卡尔坐标系内进行扩展,得到地球表面上目标运动转移概率的数学描述;接下来借助坐标转换原理和曲面积分方法,提出了大地坐标系下基于高斯分布的目标转移概率计算方法;最后针对卫星对地移动目标搜索中的目标运动预测问题,采用高可信的卫星轨道数据建立了仿真场景进行验证.仿真统计结果显示:文章提出的目标运动预测方法是有效的,在移动目标优化搜索计划的制定过程中,能够降低系统的不确定性和搜索的盲目性.
The unknown motion parameters of the target bring uncertainties to the optimization search of moving targets, which restricts the development of optimized search plans and reduces the efficiency of the use of reconnaissance and surveillance resources.In order to reduce the impact of uncertainty introduced by the target motion and the auxiliary target optimization search plan Aiming at the problem of target motion prediction in geodetic coordinate system, firstly, the motion of the target is analyzed in plane Cartesian coordinate system, and a target transfer probability density function based on Gaussian distribution is derived; then, the motion is carried out in a three-dimensional Cartesian coordinate system Then, a mathematical description of the probability of target motion transition on the Earth’s surface is obtained. Then, based on the principle of coordinate transformation and surface integral method, a method for calculating the target transition probability based on Gaussian distribution in geodetic coordinate system is proposed. Finally, The simulation scenario shows that the target motion prediction method proposed in this paper is effective and can reduce the number of targets in the process of formulating the optimal search plan System Uncertainty and Search Blindness Sex.