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基于ST-UKF的高动态GPS载波参数估计 被引量:2
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作者 王小会 李晓青 薛延刚 《电讯技术》 北大核心 2022年第4期503-509,共7页
为了克服高动态引起的多普勒效应,解决传统跟踪环路容易失锁的问题,提出了一种基于强跟踪无迹卡尔曼滤波(Strong Tracking Unscented Kalman Filter,ST-UKF)参数估计器的高动态全球定位系统(Global Positioning System,GPS)载波跟踪环路... 为了克服高动态引起的多普勒效应,解决传统跟踪环路容易失锁的问题,提出了一种基于强跟踪无迹卡尔曼滤波(Strong Tracking Unscented Kalman Filter,ST-UKF)参数估计器的高动态全球定位系统(Global Positioning System,GPS)载波跟踪环路,采用非线性滤波算法取代了传统GPS载波跟踪环路结构中的环路滤波器。此外,设计了ST-UKF参数估计器,应用该方案分别在高动态、高载噪比和高动态、低载噪比环境下对高动态GPS载波进行跟踪,并应用多个非线性算法在高动态GPS载波跟踪环路中进行比对。实验结果表明,随着环路载噪比的增大,从20 dB-Hz至30 dB-Hz,ST-UKF参数估计器对相位、多普勒频率及其一阶、二阶导数估计的均方根误差分别减小1.2192 rad、2.8805 Hz、8.9590 Hz/s和17.4803Hz/s ^(2),证明了ST-UKF参数估计器的有效性,以及跟踪环路可以完成高动态GPS载波跟踪。 展开更多
关键词 全球定位系统 载波跟踪 强跟踪无迹卡尔曼滤波(st-ukf) 高动态
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A strong tracking nonlinear robust filter for eye tracking 被引量:9
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作者 Zutao ZHANG Jiashu ZHANG 《控制理论与应用(英文版)》 EI 2010年第4期503-508,共6页
Non-intrusive methods for eye tracking are important for many applications of vision-based human computer interaction.However,due to the high nonlinearity of eye motion,how to ensure the robustness of external interfe... Non-intrusive methods for eye tracking are important for many applications of vision-based human computer interaction.However,due to the high nonlinearity of eye motion,how to ensure the robustness of external interference and accuracy of eye tracking pose the primary obstacle to the integration of eye movements into today's interfaces.In this paper,we present a strong tracking unscented Kalman filter (ST-UKF) algorithm,aiming to overcome the difficulty in nonlinear eye tracking.In the proposed ST-UKF,the Suboptimal fading factor of strong tracking filtering is introduced to improve robustness and accuracy of eye tracking.Compared with the related Kalman filter for eye tracking,the proposed ST-UKF has potential advantages in robustness and tracking accuracy.The last experimental results show the validity of our method for eye tracking under realistic conditions. 展开更多
关键词 Eye tracking Strong tracking unscented Kalman filter (st-ukf) Unscented Kalman filter (UKF) Strong tracking filtering (STF)
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