1) finite-difference extended Kalman filter(FDEKF)
有限差分卡尔曼滤波
1.
Based on guidance scheme of antagonism against the radar stopping radiating using the strapdown inertial navigation system and antiradar seeker,the application of finite-difference extended Kalman filter(FDEKF) to passive localization of target is studied.
基于捷联惯导/反辐射导引头组合抗目标雷达关机制导方案,研究了有限差分卡尔曼滤波(FDEKF)方法在对目标雷达被动定位中的应用。
2) CDKF
中心差分卡尔曼滤波
1.
In view of that there exist some defects when the Extend Kalman Filter(EKF) is employed in the vehicle integrated navigation,the Central Difference Filter(CDKF) as a new nonlinear filtering method is applied to the nonlinear state estimation of the vehicle integrated GPS/DR navigation systems.
针对扩展卡尔曼滤波(EKF)在车辆导航中存在着计算复杂、线性化误差大等缺点,将一种新的非线性滤波方法———中心差分卡尔曼滤波(CDKF)用于车辆GPS/DR组合导航中。
2.
The Central Difference Filter (CDKF) as a new nonlinear filtering method is applied to the nonlinear state estimation of the vehicle integratedGPS/DR navigation systems.
本文将一种新的非线性滤波方法——中心差分卡尔曼滤波(CDKF)刚于车辆GPS/DR组合导航中。
3.
In addition,The Central Difference Filter(CDKF) as a new nonlinear filtering method is applied to the nonlinear state estimation of the vehicle navigation systems.
接着,本文将一种新的非线性滤波方法——中心差分卡尔曼滤波(CDKF)用于车辆导航中,进行了仿真试验研究。
3) central difference Kalman filter(CDKF)
中心差分卡尔曼滤波器
4) robust Kalman filtering
抗差卡尔曼滤波
1.
Robust Kalman Filtering Model and Its Application in GPS Monitoring Networks;
抗差卡尔曼滤波模型及其在GPS监测网中的应用
2.
In order to overcome the influence of gross errors in observation vectors on the filtering values of state vectors, based on the laws that the gross errors influence the state vectors and the characteristic that they are shown completely in residual forecasting, a robust Kalman filtering model was derivesd.
为克服观测向量中的粗差对状态参数滤波值的影响 ,通过分析其影响规律 ,并充分顾及到粗差在预测残差中得到全部反映的特点 ,导出了 GPS监测网动态数据处理的抗差卡尔曼滤波模型——该模型对观测空间和设计空间均具有良好的抗差性 。
5) decentralized Kalman filter
分散卡尔曼滤波
6) an algorithm of coupled finite element and Kalman filtering
有限元与卡尔曼滤波耦合算法
1.
This paper suggests a method for estimation of distribution, deterministic and stocjastic parameters of groundwater flow system: an algorithm of coupled finite element and Kalman filtering.
提出一种估计地下水流系统分布型确定性 -随机性参数的方法 :有限元与卡尔曼滤波耦合算法。
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