1) extended Kalman filter
推广卡尔曼滤波
1.
Based on Extended Kalman Filter Position Sensorless Control for Permanent Magnet Synchronous Motor;
基于推广卡尔曼滤波的永磁同步电机无位置传感器控制
2.
To satisfy the high accuracy of attitude determination for three-axis stabilized geostationary meteorological sat- ellite image navigation,a new approach combined gyro with star sensors is proposed,and a real-time algorithm for aiti- tude estimation combined predictive filter and extended Kalman filter is designed.
为了满足三轴稳定静止气象卫星图像导航中姿态确定的高精度要求,提出了陀螺仪和星敏感器的组合定姿方案,并且设计了联合采用预测滤波和推广卡尔曼滤波的实时姿态估计算法。
3.
This oaoer oresebts an approach of position sensorle4ss control for permanent magnet synchronous motor(PMSM)based on extended Kalman filter(EKF).
介绍了一种基于推广卡尔曼滤波算法的永磁同步电机无位置传感器控制方案。
2) EKF
推广卡尔曼滤波
1.
An EKF(Extended Kalman Filter) algorithm is discussed which adds PRC(Phase Rate of Change) information.
本文探讨了一种融入相位变化率(PRC)信息的推广卡尔曼滤波(EKF)算法,通过仿真,分析了DOA与PRC单独测量与联合测量对定位精度的影响,同时,将融入PRC信息的EKF定位算法与只测角定位算法进行了比较。
2.
It also adopts the time-varying sampling modified gain extended Kalman filter(MGEKF),and shipborne ESM equipment of multiple warships are used to distributed bearings-only tracking fusion multiple maritime moving emitters.
提出一种基于信息融合的分布式多舰无源定位算法,该算法通过属性关联和空间关联相结合的方法实现了多舰无源传感器的定位关联,并采用时变采样间隔的修正增益推广卡尔曼滤波器,用多条舰艇的舰载电子侦察设备对海上多个运动辐射源目标进行分布式纯方位跟踪融合。
3.
UKF solves the problem of non-linearity of observation model better, and its performance is superior to that of EKF.
与推广卡尔曼滤波器(EKF)相比,UKF能更好解决量测模型非线性问题,滤波性能更好,而且UKF的计算量与EKF是同阶的。
4) Extended Federated Kalman Filtering
联合推广卡尔曼滤波
5) extended Kalman filter
推广的卡尔曼滤波器
1.
In this paper, the parameters and states of the non-linear PMSM system are estimated with extended Kalman filter.
本文在得到系统模型的基础上,利用推广的卡尔曼滤波器对非线性的永磁同步电动机系统参数和状态进行了估计,仿真结果验证了估计方法在数学上的可行性。
6) adaptive extended kalman filter
自适应推广卡尔曼滤波
1.
Concerning the problem of instability and low accuracy of passive filter in underwater target tracking,a modified adaptive extended kalman filter(MAEKF) algorithm is presented.
针对在被动方式下进行水下目标跟踪容易导致滤波发散和收敛精度不高的问题 ,介绍了一种改进的自适应推广卡尔曼滤波算法。
2.
In this paper,we present an adaptive extended Kalman filter(AEKF) algorithm aiming at the issues such as divergence,slow convergence and low precision of filters in passive targets tracking.
针对被动跟踪中常见的滤波发散、收敛速度慢和跟踪精度低等问题,研究了一种非线性系统的自适应推广卡尔曼滤波算法。
补充资料：卡尔曼滤波
见波形估计。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条