UKF:无气味卡尔曼滤波器
“无气味卡尔曼滤波器”(Unscented Kalman Filter,简称UKF)是一种常用于非线性系统状态估计的数学工具,广泛应用于自动控制、信号处理等工程与科研领域。该名称中的“无气味”并非指嗅觉概念,而是强调该方法无需对非线性函数进行线性化近似,从而保持更高的精度与稳定性。为便于书写和交流,学界普遍使用其英文缩写UKF。
Unscented Kalman Filter具体释义
Unscented Kalman Filter的英文发音
例句
- After analyzing the model of high dynamic signals, a quasi-open-loop carrier tracking method based on unscented Kalman filter ( UKF ) is proposed.
- 在分析高动态载波信号模型的基础上,提出了一种基于无迹卡尔曼滤波(UKF)的准开环载波跟踪方法。
- Method for radar target tracking based on sequential unscented Kalman filter
- 基于序贯无迹卡尔曼滤波的雷达目标跟踪方法
- This paper presents a real-time background subtraction and moving shadow detection method based on Unscented Kalman Filter(UKF) ( UKF ), and constructs the whole frame for moving object detection.
- 提出了基于无偏卡尔曼滤波器(UKF)的背景提取和阴影检测方法,构建整体的运动物体检测框架。
- This algorithm adopts the weight control parameter to decide whether the particle enters unscented Kalman filter, thus decreasing filtering computing amount and having the same precision of UPF.
- 该算法采用权值控制参数决定粒子是否进入平淡卡尔曼滤波器,有效降低了滤波计算量,并和UPF算法精度相当。
- In view of nonlinear feature of measure equation, a ground target tracking algorithm based on the unscented kalman filter ( UKF ) is given. Finally, the simulation experiment is analyzed.
- 针对雷达测量模型非线性的特点,提出了基于无迹卡尔曼滤波UKF算法的地面目标跟踪算法,并进行了仿真试验分析。
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