基于高斯和SCKF的姿态角辅助三维目标跟踪  

Pose angle aided 3D target tracking based on Gaussian sum square-root cubature Kalman filter

作　　者：张凯[1] 单甘霖[1] 

机构地区：[1]军械工程学院电子与光学工程系,石家庄050003

出　　处：《控制与决策》2015年第1期46-52,共7页Control and Decision

基　　金：国防预研基金项目(513270203)

摘　　要：首先,根据目标运动与姿态角的关系,分析目标在偏航角和俯仰角下的速度变化,进而推导出姿态角辅助三维目标跟踪模型;然后,针对姿态角量测非高斯情况,在分析均方根容积卡尔曼滤波的基础上,提出新的高斯和均方根容积卡尔曼滤波算法,以提高非线性非高斯的处理能力;最后,结合不同运动模式下姿态角分量的特点,建立姿态角分量不同的跟踪模型,通过模型切换实现对姿态角机动的跟踪.仿真结果验证了所提出跟踪模型和滤波算法的正确性和有效性.Pose angle aided 3D target tracking models are derived based on the analysis of target velocity variation under the yaw and pitch angle, with the relationship between the pose angle and the motion. Aiming to the non-Gaussian characteristic of pose angle measurements, the Gaussian sum square-root cubature Kalman filter（GSSCKF） is proposed based on the analysis of square-root cubature Kalman filter（SCKF）, and the filtering ability of non-Gaussian nonlinear is improved. According to the pose angle variation law during target motion, tracking models with different pose angle components are established, and the maneuvering pose angle is estimated by model switch. The simulation results show the effectiveness and correctness of the tracking model and the filtering algorithm.

关 键 词：目标跟踪 均方根容积卡尔曼滤波 高斯和滤波 模型切换 

分 类 号：TP95[自动化与计算机技术]