研究了三维系统偏差条件下的扩维目标跟踪问题,提出了一种基于扩展卡尔曼滤波器的目标状态与系统偏差的联合估计算法,并在此基础上探讨了三种系统偏差条件下状态估计的初始化方法。Monte-Carlo仿真表明,ASEKF算法能有效地对目标状态和系统偏差进行实时联合估计。
The problem that how to track a three-dimensional target with systematic errors is researched in this paper. Using the extended Kalman filter, an augmented state extended Kalman filter(ASEKF) algorithm for joint estimation of state and systematic errors is proposed. In order to initializes the state estimation, three methods is derived. The Monte-Carlo simulation results show that the ASEKF algorithm can estimate efficiently.