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AMAUKF应用于无人机跟踪目标再捕获研究 被引量：4

Application of AMAUKF on the Condition of Target Re-Tracked by UAV
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摘要 无人机(UAV)在使用滤波器对目标跟踪时常遇到目标丢失情况,然而在目标丢失时使用一步估计代替估计值会对跟踪精度造成较大影响,鉴于此,将自适应衰减记忆滤波(AMAF)理论应用于无迹卡尔曼滤波(UKF)以提高再次捕获目标后的跟踪精度;新的滤波器命名为自适应衰减记忆卡尔曼滤波(AMAUKF);在此基础上设计了滤波流程和计算机仿真实验,结果表明新的滤波器不但缩短了收敛步长,而且提高了跟踪精度。 UAV tracking target always face the target-lost event.However,filter used to consider one-step prediction as estimation when target lost event happening,which cause bad influence to precision of tracking.For that reason,applying the Self-Adaptive Memory Attenuated Filter theory to UKF could increase the tracking precision after target re-tracked by UAV.The new filter is named as Adaptive Memory Attenuated Unscented Kalman Filter（AMAUKF）.Based on this new filter,it designs the filter running flow and computer experiment,which show the new filter shorten the step of convergence and advance the precision of tracking.
作者 余霁洲 刘慧霞 刘承禹 席庆彪
机构地区 西北工业大学自动化学院 西北工业大学第 二炮装备研究院
出处 《计算机测量与控制》 CSCD 北大核心 2012年第2期516-519,共4页 Computer Measurement &Control
基金 国家自然科学基金(61074155)
关键词 无人机 无迹卡尔曼滤波 自适应衰减记忆滤波器 目标丢失事件 不完全量测 自适应衰减记忆无迹卡尔曼滤波滤波器 UAV UKF target lost event incomplete measurement adaptive memory attenuated unscented Kalman filter（AMAUKF）
分类号 TN593 [电子电信]
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共引文献329

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计算机测量与控制
2012年 第2期

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