大地坐标系下目标运动预测:一种基于高斯分布的求解方法

Motion prediction in geodetic coordinate systems:A solution based on Gaussian distribution

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 parameters of moving target bring uncertainty to moving target search which constrains the optimal search plan making and impairs surveillance assets efficiency.Motion prediction in geodetic coordinate systems,as a way to depress the effect of uncertainty and to optimize the search plan,is well discussed：firstly,moving target motion in plane Cartesian coordinate systems is analyzed and a Gaussian distribution of target transition probability density function（PDF） is deduced;secondly, the PDF is extended to denote target transition probability in 3-D Cartesian coordinate;thirdly,the method for computing the target transition probability in geodetic coordinate systems based on Gaussian distribution is deduced by coordinate systems transformation and curved surface integral method;finally,a simulation scenario with high fidelity satellite orbit data is utilized to verify the motion prediction algorithm in the problem of moving target search by satellite.The simulation performance statistics show that the prediction algorithm is effective which can decrease the uncertainty and reduce the eyeless search during making search plan.