论文标题
分析基于优化的绩效标准仅目标跟踪算法
Analysis of performance criteria for optimization based bearing only target tracking algorithms
论文作者
论文摘要
目标跟踪问题在现实生活中具有许多实际应用。在潜艇中，目标跟踪是使用被动传感器完成的。这些传感器仅测量观察到的目标与自身职责之间的轴承角。因此，此问题通常称为仅承载目标跟踪或目标运动分析。经典的方法是使用基于状态观察者的过滤器，即扩展的Kalman滤波器，以估算目标的范围，过程和速度，仅使用轴承。在最近的研究中，通过利用进化算法在某些客观功能方面，该问题被解决为全球优化问题。在这项研究中，我们研究了常用成本函数对TMA算法性能的影响。特别是，我们根据轴承差异和等距线段的成本功能研究成本功能。模拟结果表明，与前者相比，后者为目标运动分析问题提供了亚最佳解决方案。
Target tracking problem has many practical applications in real life. In submarines, target tracking is done using, preferably, passive sensors. These sensors measure only the bearing angles between the observed target and the ownship. Therefore, this problem is generally referred as bearing only target tracking or target motion analysis. The classical approach is to use a state observer based filter, i.e. Extended Kalman Filter, to estimate the range, course and speed of the target, using only the bearings. In recent studies, the problem is solved as a global optimization problem by utilizing evolutionary algorithms with respect to some objective functions. In this study, we investigate the effect of the commonly used cost functions on the performance of the TMA algorithms. Particularly, we investigate the cost functions based on bearing differences and equidistant line segments. The simulation results show that the latter gives a sub-optimal solution to the target motion analysis problem, compared to the former.
