摘要
针对杂波环境下标准的势均衡多伯努利滤波器不能有效跟踪多机动目标的问题,本文提出了一种新的多机动目标跟踪算法。该方法将势均衡多伯努利滤波器与"当前"统计自适应模型相结合,对目标的运动状态矩阵进行扩维,改变了目标状态转移矩阵和过程噪声方差,增加控制矩阵,实现目标加速度的自适应调整,从而使新算法能够适应目标运动状态的变化。仿真结果表明,在机动条件下,新算法能有效地跟踪多机动目标,而且跟踪精度较高。
Considering that the standard Cardinality Balanced Multi-Target Multi-Bernoulli（CBMe MBer） filter cannot track multiple maneuvering targets effectively in the clutter environment, a new tracking algorithm of maneuvering targets is proposed, which combines the CBMe MBer filter with the adaptive current statistical model. In the new algorithm, the dimension of the target state vector is augmented, the state transition matrix and the process noise covariance are adjusted, and the control matrix is attached. Then the targets＇ acceleration can be adjusted adaptively. Finally, the new algorithm can adapt to the change of the targets＇ moving state. Simulation results show that the proposed algorithm can track multiple maneuvering targets effectively, which has higher tracking accuracy in the maneuvering condition.
出处
《光电工程》
CAS
CSCD
北大核心
2015年第10期7-12,共6页
Opto-Electronic Engineering
基金
国家自然科学基金项目(61201118)
中国博士后科学基金项目(2103M532020)
陕西省教育厅科研计划项目(15JK1291)
西安工程大学学科建设项目
