1) unscented Kalman filter
无味卡尔曼滤波
1.
Then we studied the tracking problem of multiple maneuvering targets by using the combination of interacting multi-model and unscented Kalman filter algorithm.
在此基础上,采用交互式多模型算法和无味卡尔曼滤波相结合的方法研究了多机动目标的跟踪问题。
2.
Unscented Kalman filter was chosen as the relative navigation filter.
首先建立了适用于目标航天器运行在椭圆轨道上的二阶状态方程;分析了2个航天器间的量测几何关系并得到量测方程;采用适用于处理复杂非线性模型的无味卡尔曼滤波器进行相对导航计算。
3.
The unscented Kalman filter(UKF) is applied to the radar registration and a new algorithm for the multi-radar azimuth registration is presented.
将无味卡尔曼滤波(U nscen ted K a lm an filter,UKF)应用于雷达配准,提出一种新的多雷达方位配准算法。
2) unscented kalman filtering
无味卡尔曼滤波
1.
The problem of target motion analysis based on bearing and Doppler measurements(BDO-TMA)is studied contrastively by means of unscented kalman filtering(UKF)and extended kalman filtering(EKF)algorithms.
针对空对海单站无源只测方位-多普勒目标运动分析(BDO-TMA)问题应用无味卡尔曼滤波(UKF:Unscented Kalman Filtering)和EKF进行了对照研究,建立了该应用场景下的离散非线性滤波估计模型,Monte Carlo仿真运行结果表明,UKF在该应用背景下是切实可行的,具有更高的估计精度和更强的收敛特性。
2.
Simulation study based on unscented kalman filtering for the impact of data rate in the bearing-only target motion analysis;
应用无味卡尔曼滤波(UKF)来解决只测方位目标运动分析(BO-TMA)问题,研究了其中数据率因素的实际影响。
3) unscented Kalman filter
无味卡尔曼滤波器
1.
By analyzing the error of unscented Kalman filter(UKF),the iterated UKF(IUKF) algorithm is proposed.
通过对无味卡尔曼滤波器(Unscented Kalman filter,UKF)的误差进行分析,提出了迭代UKF(IUKF)算法。
4) Unscented kalman filter(UKF)
无迹卡尔曼滤波
1.
The unscented Kalman filter(UKF) model for the system is built up,and a numerical simulation is performed with the software Matlab.
设计了一种采用陀螺罗经和多普勒速度仪组合加GPS间歇校正的水下航行器组合导航系统,建立了该组合导航系统的无迹卡尔曼滤波模型,并利用MATLAB软件对其进行了数学仿真验证。
2.
We aim to eliminate these shortcomings as much as possible with a different and we believe better method by using the unscented Kalman filter(UKF) based SLAM(simultaneous localization and mapping) technique.
针对应答器未校准情况下的水下长基线定位问题,提出了基于无迹卡尔曼滤波的同步定位与地图创建方法。
3.
Its core consists of:(1) we design a variable structure sliding-mode speed controller and a variable structure sliding -mode current controller to replace the traditional speed PI controller and two current PI controllers;(2) we design the unscented Kalman filter(UKF) observer to estimate direct-axis current,quadrature-axis current,load torque,rotor position and speed simultaneously.
针对电机控制中采用的PI调节器对电机参数变化及外加干扰时鲁棒差和无位置传感器控制实现困难等问题,在研究常规永磁同步电机矢量控制策略的基础上,将滑模变结构控制(VSSMC)和无迹卡尔曼滤波(UKF)引入该策略中,用VSSMC分别替代策略中速度PI控制器和2个PI电流控制器,同时利用UKF对电机定子直轴电流、交轴电流、负载转矩、转子位置和转速进行实时估计,提出了一种新颖的基于VSSMC和UKF的永磁同步电机无传感器矢量控制方案。
5) UKF
无迹卡尔曼滤波
1.
In view of the problem that determination of relative attitude between formation satellites is difficult,a modified Unscented Kalman Filter(UKF)was adopted to design the Filter of system in the paper.
针对编队卫星相对姿态确定问题,采用一种改进的无迹卡尔曼滤波UKF进行了系统滤波器设计,根据UKF滤波器的性质,推导出了适用于编队卫星相对姿态确定的UKF滤波算法。
2.
The Standard Kalman Filter can not solve the nonlinear mathematic model,and the Extending Kalman Filter(EKF) will consume much more calculation,so Unscented Kalman Filter(UKF) is adopted in this system.
由于标准卡尔曼滤波不能处理非线性模型,而扩展卡尔曼滤波有计算量大等缺点,故采用无迹卡尔曼滤波(UKF)进行处理。
6) unscented Kalman filter
无迹卡尔曼滤波
1.
Application of unscented Kalman filter to novel terrain passive integrated navigation system;
无迹卡尔曼滤波在新型地形无源组合导航系统中的应用(英文)
2.
Based on combination of sampling importance resampling(SIR) and unscented Kalman filter(UKF),a novel particle filter is proposed,possessing the merits of high utility efficiency of particles in unscented particle filter(UPF) and of simple operation in SIR,and overcoming the drawback of the rate of increase of computational cost being faster than that of state dimension in UPF.
将采样重要再采样(SIR)方法与无迹卡尔曼滤波(UKF)相结合,提出一种新的粒子滤波算法。
3.
This paper introduces the newly proposed unscented Kalman filter (UKF).
无迹卡尔曼滤波算法(UFK)以少量的采样点表示随机变量的分布,通过非线性系统传播,能以三阶精度获得非线性变换的均值和协方差的估计。
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