欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
为解决基于“当前”统计模型的自适应滤波器对弱机动,特别是非机动目标跟踪精度下降问题,提出基于模糊神经网络的目标自适应跟踪算法,对并行工作的两滤波器进行数据融合.仿真结果表明：与一般自适应算法相比,该算法对各种机动程度的目标跟踪精度均有不同程度的提高,能更好地适应目标的各种运动形式,尤其适用于对目标的速度和加速度估计精度要求较高的场合,在指控、火控系统中具有实用价值.
英文摘要：
This paper presented a target adaptive tracking algorithm based on fuzzy neural networks to solve problem of tracking precision drop for low-maneuvering and non-maneuvering targets based on current statistic model. The method made a data fusion of two filters working in parallel. Simulation results show that the proposed algorithm can improve target-tracking accuracy for different kinds of maneuvering degree and adapt to all kinds of movement forms of the target, especially to the situation when high filtering precision for velocity and acceleration of the target is needed. It has practical value of reference for the research of fire control system and command control system.
同期刊论文项目
同项目期刊论文
期刊信息
位置：