采用扩展卡尔曼滤波实现异质传感器融合。
It utilizes extended Kalman filtering to carry out heterogeneous sensor fusion.
采用扩展卡尔曼滤波方法设计了导航滤波器。
The navigation filter was designed using extended Kalman filtering technique.
运用扩展卡尔曼滤波算法，研究了该系统的目标运动分析问题。
With the algorithm of extend Kalman filter, the target motion analysis is discussed.
对REKF和传统扩展卡尔曼滤波(ekf)的性能进行对比。
The performance of the REKF is illustrated in comparison with the standard EKF.
利用扩展卡尔曼滤波器估计这种偏差，并用估计偏差对传感器测量进行校正。
The mentioned error can be estimated by using the extended Kalman filters, and the estimated error is used for calibrating the sensor measurement.
推广了线性卡尔曼滤波算法，导出雷达混合坐标系下的扩展卡尔曼滤波算法；
The linear kalman filtering algorithm is extended under the mix coordinate of radar;
提出了采用扩展卡尔曼滤波器估计入射波参数(入射角度和入射功率)的方法。
A method for estimating the parameters of incident wave Angle and incident power by the use of the extended kalman filter is proposed.
为了提高定位精度，本文又引入扩展卡尔曼滤波算法对原始定位结果进行处理。
For improving the locating accuracy, the EKF algorithm is introduced to process the initial locating results.
应用扩展卡尔曼滤波器融合SIFT特征信息与机器人位姿信息完成SLAM。
SLAM is completed by fusing the information of SIFT features and robot information with EKF.
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。
A novel method for speed and rotor position estimation of BLDCM, which applies extend Kalman filter (EKF), is presented in this paper.
针对多基地雷达系统跟踪近距离高加速机动目标的场合，提出了一种并行扩展卡尔曼滤波算法。
To investigate the problem of tracking a high accelerating maneuvering target with netted radar system, the parallel extended Kalman filtering algorithm is derived.
设计了一种蜂窝系统无线定位中使用的扩展卡尔曼滤波(ekf)算法，对其性能进行了仿真。
An extended Kalman filtering (EKF) algorithm is designed for radiolocation in cellular communication system, simulation is conducted to examine its performance.
在水下被动目标跟踪系统中，直角坐标系下的扩展卡尔曼滤波器容易发散而导致滤波精度很差。
Concerning the problem to instability and low accuracy of the passive filter on bearings-only target tracking, a modified adaptive Extended Kalman filter algorithm on polar coordinate is presented.
目前，实现定位跟踪的算法有很多，如卡尔曼滤波算法、扩展卡尔曼滤波算法、粒子滤波算法等。
At present, there are many algorithms to achieve position tracking, such as the Kalman filter algorithm, extended Kalman filter algorithm, particle filter algorithm and so on.
最后，给出了扩展卡尔曼滤波算法、无迹卡尔曼滤波算法和粒子滤波算法的推导过程和仿真分析。
Finally, the computational procedures and simulation analysis of extended Kalman filtering algorithm, unscented Kalman filtering algorithm and particle filtering algorithm is presented.
针对该问题，本文基于扩展卡尔曼滤波方法提出了一种准最佳的GPS载波跟踪环结构设计方案。
Aiming at this problem, a new quasi-optimal structure of GPS carrier tracking loop based on extended Kalman filtering is proposed in this dissertation.
对经典的卡尔曼滤波以及针对非线性系统的扩展卡尔曼滤波，不敏卡尔曼滤波算法进行了分析比较。
The state estimations algorithm for Target tracking have been studied and compared such as Kalman filter, Extented Kalman filter and Unscented Kalman filter.
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。
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.
第三，介绍了扩展卡尔曼滤波原理，并对GPS接收机天线的布局及影响定姿精度的因素进行了分析。
Third, introduce the principle of extended Kalman filter, and analyze the layout of GPS antenna and factors which can impact the accuracy of attitude determination.
设计扩展卡尔曼滤波器进行卫星编队轨道状态估计，数学仿真结果验证了这种导航方案和算法的有效性。
The orbit states estimation is achieved through the extended Kalman filters design. The simulation results verify the validity of this navigation method, and show preferable navigation accuracy.
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。
Extended Kalman Filter (EKF) and converted measurement Kalman Filter (CMKF) have been widely used in radar target tracking.
利用单目摄像头提取和跟踪环境特征点集，进而根据观测模型利用扩展卡尔曼滤波算法估算出机器人的位姿。
It extracts and tracks feature point sets in the environment with single camera, and then calculates position and pose of the robot with measurement model and extended Kalman filtering.
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。
Based on vector control system of Bearingless Permanent Magnet Synchronous Motor (BPMSM), a speed-sensorless control strategy using Extended Kalman Filter (EKF) was presented.
利用扩展卡尔曼滤波算法估计机械手各关节的初始角位置，从而间接地保证机械手在工作空间内的绝对定位精度。
The initial angular positions of the joints are estimated by the extended Kalman filter algorithm, then the manipulator's absolute locating accuracy in its workspace is guaranteed indirectly.
综合泄漏流量的有限元计算结果与扩展卡尔曼滤波器的估计结果，与实测结果相比较，进一步完善理论分析方法。
The theoretical analysis is verified and improved by comparing the results of FEM calculation and EKF estimation with experimental measurement.
IG- 500n拥有嵌入式的扩展卡尔曼滤波器，使其在高速动态条件下能够提供无与伦比的姿态和方位测量精度。
With its embedded Extended Kalman Filter, the IG-500N delivers unmatched precision for attitude and position measurements in very high dynamic conditions.
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。
According to the similar computation process of UKF and extended Kalman filter (EKF), the combined Kalman filter based on SSUKF and EKF was designed.
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。
Unscented Kalman Filter (UKF), which is an evolutional algorithm of Extended Kalman Filter (EKF), has been successfully applied in many nonlinear estimation problems.
模块的组成、功能，详细说明了姿态角的计算、初始对准以及采用的稳定、实时、变增益自适应扩展卡尔曼滤波估计算法。
Attitude calculation techniques, initial alignment methods and a real-time adaptive extended Kalman filter used for improve the system precision were discussed.
模块的组成、功能，详细说明了姿态角的计算、初始对准以及采用的稳定、实时、变增益自适应扩展卡尔曼滤波估计算法。
Attitude calculation techniques, initial alignment methods and a real-time adaptive extended Kalman filter used for improve the system precision were discussed.
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