纯方位目标运动状态的极大似然估计及迭代算法

Maximum likelihood estimation and iterative algorithm for bearings-only target motion analysis

针对非线性最小二乘法在国内目标运动分析中应用较少的现状,首先在二维平面内推导出关于纯方位目标运动状态的极大似然估计的计算公式并给出了基于高斯-牛顿迭代算法的计算过程及步骤,随后分析了极大似然估计的性能和迭代算法的收敛性。仿真计算的结果表明:当迭代初值与目标真实状态充分接近时,用所推导出的计算公式能够快速稳定地得到关于目标运动状态的极大似然估计,迭代算法形式简洁,计算量小。该研究成果可应用于舰艇作战系统目标被动跟踪定位软件。

As non-linear least square is rarely applied in the analysis of target motion at home, a series of formulas for the maximum likelihood estimation of the bearings-only target in motion was deduced under the two-dimensional conditions. Based on Gauss-Newton iteration algorithm, the calculative process and procedures were proposed. The performance of maximum likelihood estimation and the convergence of iteration algorithm were analyzed. The simulation results show that the method can be used for estimating the parameters of bearings-only target motion in a rapid and steady way, when the initial value of iteration is sufficiently close to the true target state. The iterative algorithm is simple in form with less amount of calculation.