By using the forming filter and EKF, the precision of states estimation is increased and a effective estimation of stochastic sea interference is performed.
通过引入成型滤波器，采用EKF，提高了状态估计的精度，实现对随机海浪扰动力和力矩的估计。
When the estimated error of gyro drift reduces to some low extent, the filter was switched to the fusion mode of EKF and optimal REQUEST.
当陀螺漂移误差减小到一定程度，再切换为EKF与最优REQUEST算法融合的双重滤波器。
Using UD decomposing to modify EKF Particle filter was imported into the navigation scheme based on the measurement of elevation Angle of star.
用UD分解改进EKF粒子滤波算法，并将其应用于基于星光仰角测量的探测器自主导航方案。
According to the similar computation process of UKF and extended Kalman filter (EKF), the combined Kalman filter based on SSUKF and EKF was designed.
根据UKF和扩展卡尔曼滤波(ekf)计算过程相似的特点，设计了SSUKF和EKF相结合的混合卡尔曼滤波算法。
In state estimation of satellite attitude determination, both traditional extended Kalman filter (EKF) and the proposed nonlinear predictive filter (NPF) have their own merits and defects.
在确定卫星姿态确定的状态估计法中，经典的扩展卡尔曼滤波(ekf)和新提出的非线性预测滤波(NPF)这两种实时滤波算法各有优缺点。
A novel method for speed and rotor position estimation of BLDCM, which applies extend Kalman filter (EKF), is presented in this paper.
本文提出了一种利用扩展卡尔曼滤波器算法来估计BLDCM的转速和位置的方法。
The application of the Extended Kalman Filter (EKF) to identify INS platform drift error coefficients under the condition of ideal and nonideal linear vibration is presented.
设计了多位置测漂方案，利用扩展卡尔曼滤波对理想、非理想线振动条件下的参数辨识问题进行仿真。
Extended Kalman Filter (EKF) and converted measurement Kalman Filter (CMKF) have been widely used in radar target tracking.
在雷达目标跟踪中，扩展卡尔曼滤波(ekf)和转换坐标卡尔曼滤波(CMKF)得到了广泛的应用。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
无轨迹卡尔曼滤波器(ukf)作为扩展卡尔曼滤波器(ekf)的进化算法在许多非线性估计问题上取得了成功的应用。
Based on vector control system of Bearingless Permanent Magnet Synchronous Motor (BPMSM), a speed-sensorless control strategy using Extended Kalman Filter (EKF) was presented.
基于无轴承永磁同步电机的矢量控制系统，提出了采用扩展卡尔曼滤波器实现无速度传感器运行的控制策略。
This paper presents a hybrid model for urban arterial travel time prediction based on the so-called state space neural networks (SSNN) and the extended Kalman Filter (EKF).
提出了一种基于状态空间神经网络(SSNN)和拓展卡尔曼滤波(ekf)的混合式行程时间预测模型。
The extended Kalman filter(EKF) and converted measurement Kalman filter(CMKF) have been widely used in radar target tracking.
在非线性量测的情况下，EKF和CMKF得到了广泛的应用。
The application of the Extended Kalman Filter (EKF) to identify INS platform drift error coefficients under the condition of ideal and non-ideal linear vibration is presented in this paper.
设计了多位置测漂方案，对理想、非理想线振动条件下的参数辨识问题进行了仿真。
The application of the Extended Kalman Filter (EKF) to identify INS platform drift error coefficients under the condition of ideal and non-ideal linear vibration is presented in this paper.
设计了多位置测漂方案，对理想、非理想线振动条件下的参数辨识问题进行了仿真。
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